Smart-home system facilitating insight into detected carbon monoxide levels

ABSTRACT

In an embodiment, a method determines one or more sources of carbon monoxide (CO) in a smart-home environment that includes a plurality of smart devices that have at least measurement and communication capabilities. The method includes measuring a level of CO in the smart-home environment to generate a CO measurement, and providing the CO measurement and one or more current characteristics of the smart-home environment, from one or more of the smart devices to an analyzing device. The method further includes evaluating, by the analyzing device and with the CO measurement and the current characteristics of the smart-home environment, a set of CO correlation scenarios that attribute generation of CO to a corresponding one of a set of specific sources, and selecting one or more of the specific sources as the most likely source of the CO, by aggregating results of the correlation scenarios.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority to U.S. ProvisionalPatent Application Ser. No. 61,887,969, filed 7 Oct. 2013, entitled“User-Friendly Detection Unit,” and U.S. Provisional Patent ApplicationSer. No. 61,887,963, filed 7 Oct. 2013, entitled “Hazard Detection in aSmart-Sensored Home.” The above-identified patent applications arehereby incorporated by reference herein in their entireties for allpurposes.

TECHNICAL FIELD

This patent specification relates to systems, devices, methods, andrelated computer program products for providing hazard-detectionobjectives. More particularly, this patent specification relates to aplurality of devices, including intelligent, multi-sensing,network-connected hazard detection units or smart hazard detectors(e.g., smoke detectors, carbon monoxide detectors, etc.), thatcommunicate with each other and/or with a central server or acloud-computing system to provide any of a variety of hazard-detectionobjectives that are useful in smart building and smart-homeenvironments.

BACKGROUND OF THE INVENTION

Some homes today are equipped with smart-home networks to provideautomated control of devices, appliances and systems, such as heating,ventilation, and air conditioning (“HVAC”) systems, lighting systems,alarm systems, and home theater and entertainment systems. Smart-homenetworks may include control panels that a person may use to inputsettings, preferences, and scheduling information that the smart-homenetwork uses to provide automated control the various devices,appliances and systems in the home. For example, a person may input adesired temperature and a schedule indicating when the person is awayfrom home. The home automation system uses this information to controlthe HVAC system to heat or cool the home to the desired temperature whenthe person is home, and to conserve energy by turning offpower-consuming components of the HVAC system when the person is awayfrom the home. Also, for example, a person may input a preferrednighttime lighting scheme for watching television. In response, when theperson turns on the television at nighttime, the home automation systemautomatically adjusts the lighting in the room to the preferred scheme.

Additionally, many homes today are equipped with hazard detectors, suchas smoke detectors and carbon monoxide detectors. Some of these homeshave multiple hazard detectors, where each hazard detector is configuredto sound an alarm upon detecting a hazardous condition. Upon hearing analarm, occupants of these homes may have to search the home to locatethe detector that is sounding the alarm to determine whether the alarmis false or whether a hazardous condition actually exists. This can betime-consuming, stressful, and potentially dangerous. Oftentimes thealarm is false. For example, smoke detectors located near bathrooms maymistake shower steam as smoke. Similarly, smoke detectors located in ornear kitchens may mistake steam from boiling water as smoke. Also, smokedetectors located in or near kitchens may provide a large number offalse alarms due to their over sensitivity to moderate smoke levelscommon to kitchens.

To avoid the nuisance of false alarms, occupants may disable hazarddetectors, such as by removing the batteries or disconnecting the powersupply. Disabled or otherwise ineffective hazard detectors result inpreventable accidental home deaths. For example, people die each year inhome fires, such as fires caused by occupants who fall asleep whilesmoking cigarettes, because the hazard detectors in their homes weredisabled, or because the hazard detectors malfunctioned or wereimproperly installed. Also, for example, carbon monoxide (CO) poisoningkills approximately one thousand people per year, a lot of whom arechildren. It is likely that properly functioning CO detectors would haveprevented some of these deaths. Accordingly, there is a need forimproved hazard detectors for homes and buildings.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the invention provide methods and systems forfacilitating the provisioning, set-up, configuration, control, and/ormanagement of intelligent, network-connected, multi-sensing hazarddetection units or smart hazard detectors. These smart hazard detectorsmay be used within a home, building, or structure to warn occupants ofthe home, building, or structure of potentially hazardous conditions.

In an embodiment, a method for controlling a climate control system of asmart-home environment that includes a plurality of smart devices isprovided. The method includes detecting, with a hazard detector of thesmart devices, a level of carbon monoxide (CO) at the hazard detectorthat exceeds a threshold CO level at a location of the hazard detector,determining, by one of the smart devices, that the climate controlsystem includes a combustion based heat source, and in response to thedetecting and the determination, transmitting, by a system controller ofthe climate control system, a first signal to turn off at least oneaspect of the climate control system.

In an embodiment, a smart-home environment is provided, that includes aclimate control system responsive to signals from a system controllerand including a combustion based heat source, and a plurality of smartdevices configured for wireless communication amongst themselves. Thesmart devices include at least a hazard detector that is configured tomeasure a level of carbon monoxide (CO) at a location of the hazarddetector, and the system controller. The system controller is configuredto transmit a signal to turn off at least one aspect of the climatecontrol system responsive to the hazard detector detecting a level of COat that exceeds a threshold CO level at a location of the hazarddetector.

In an embodiment, a method for controlling a climate control system of asmart-home environment that includes a plurality of smart devices isprovided. The method includes detecting, by a hazard detector of thesmart devices, a level of carbon monoxide (CO) at the hazard detectorthat exceeds a threshold CO level at a location of the hazard detector,determining, by one of the smart devices, that the level of CO at thehazard detector may be associated with operation of the climate controlsystem, and in response to the detecting and the determination,transmitting, by a controller of the smart devices, a first signal toturn off at least one aspect of the climate control system.

In an embodiment, a method determines one or more sources of carbonmonoxide (CO) in a smart-home environment that includes a plurality ofsmart devices that have at least measurement and communicationcapabilities. The method includes measuring a level of CO in thesmart-home environment, by one of the smart devices, to generate a COmeasurement, and providing the CO measurement and one or more currentcharacteristics of the smart-home environment, from one or more of thesmart devices to an analyzing device. The method further includesevaluating, by the analyzing device and with the CO measurement and thecurrent characteristics of the smart-home environment, a set of COcorrelation scenarios that attribute generation of CO to a correspondingone of a set of specific sources, and selecting one or more of thespecific sources as the most likely source of the CO, by aggregatingresults of the correlation scenarios.

To better understand the nature and advantages of the present invention,reference should be made to the following description and theaccompanying figures. It is to be understood, however, that each of thefigures is provided for the purpose of illustration only and is notintended as a definition of the limits of the scope of the presentinvention. Also, as a general rule, and unless it is evident to thecontrary from the description, where elements in different figures useidentical reference numbers, the elements are generally either identicalor at least similar in function or purpose.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example of a smart-home environment within which one ormore of the devices, methods, systems, services, and/or computer programproducts described further herein will be applicable, according to anembodiment;

FIG. 2 illustrates a network-level view of an extensible devices andservices platform with which the smart-home environment of FIG. 1 can beintegrated, according to an embodiment;

FIG. 3 illustrates an abstracted functional view of the extensibledevices and services platform of FIG. 2, with reference to a processingengine as well as devices of the smart-home environment, according to anembodiment;

FIG. 4 illustrates a perspective exploded view of an intelligent,multi-sensing, network-connected hazard detector, according to anembodiment;

FIGS. 5A and 5B illustrate front and rear perspective views of a circuitboard of the hazard detector of FIG. 4, according to an embodiment;

FIG. 6 illustrates a method 1300 for setting up a hazard detector andpairing the hazard detector and an online management account, accordingto an embodiment;

FIGS. 7-11 illustrate examples of the physical process associated withthe method of FIG. 6, according to an embodiment;

FIG. 12 illustrates a method for pairing two or more hazard detectorsand an online management account, according to an embodiment;

FIG. 13 illustrates visual vocabulary for visual effects that may beused by a hazard detector, according to an embodiment;

FIG. 14 illustrates an animation/color matrix of visual effects that maybe used by hazard detector, according to an embodiment;

FIG. 15 illustrates an audible low-battery warning, according to anembodiment;

FIG. 16 illustrates a method for setting pre-alarm thresholds for ahazard detector based at least in part on where the hazard detector islocated, according to an embodiment;

FIG. 17 provides a data table of example thresholds used by hazarddetector to determine whether pre-alarm conditions exist, according toan embodiment;

FIG. 18A illustrates a method for providing a “normalcy” message when analarm condition has cleared from a location, according to embodiments;

FIG. 18B illustrates a method of establishing alarm codes within smartdevices of a smart-home environment, according to embodiments;

FIG. 19 illustrates a method of controlling an HVAC fan to at leastpartially ameliorate hazardous conditions, according to an embodiment;

FIG. 20A illustrates a method of determining a cause of a high COcondition in a smart-home environment and, when appropriate, altering atleast one aspect of the home environment to at least partiallyameliorate the high CO condition, according to an embodiment;

FIG. 20B is a flowchart illustrating a method 2900 for determining oneor more sources of CO in a smart-home environment, according to anembodiment;

FIG. 20C shows a table illustrating possible correlation scenarios foridentifying CO sources, according to an embodiment;

FIG. 20D illustrates a method of setting a pre-hazardous CO alarmthreshold for a smart-home environment, according to an embodiment;

FIG. 20E illustrates a method of setting multiple pre-hazardous CO alarmthresholds for a smart-home environment, according to an embodiment;

FIG. 21 illustrates an exemplary environment with which embodiments maybe implemented with a computer system that can be used by a user toremotely control, for example, one or more of the sensor-equippedsmart-home devices, according to one or more embodiments;

FIG. 22 schematically illustrates an embodiment in the form of aspecial-purpose computer system;

FIG. 23 illustrates interaction of a user with a smart hazard detectorto deactivate or “hush” an alarm, according to an embodiment;

FIG. 24 illustrates interaction of a user with a smart hazard detectorto deactivate or “hush” an alarm, according to an embodiment;

FIGS. 25A and 25B schematically illustrate, in front and perspectiveviews respectively, an intelligent, multi-sensing, network connectedthermostat, according to an embodiment; and

FIG. 26 is a schematic diagram illustrating geo-fencing, according to anembodiment.

DETAILED DESCRIPTION OF THE INVENTION

The present invention will now be described in detail with reference tocertain embodiments thereof as illustrated in the accompanying drawings.In the following description, numerous specific details are set forth inorder to provide a thorough understanding of the present invention. Itwill be apparent, however, to one skilled in the art, that the presentinvention may be practiced without some or all of these specificdetails. In other instances, well known details have not been describedin detail in order not to unnecessarily obscure the present invention.

Overview of the Smart-Home Environment

Provided according to one or more embodiments are methods and systemsfor setting up, controlling, and/or programming one or more ofintelligent, network-connected, multi-sensing hazard detection units orsmart hazard detectors. These smart hazard detectors may be configuredand adapted to be implemented in a smart-home environment, seamlesslyinteracting with other devices in the smart-home environment. The term“smart hazard detector” is used herein to represent a particular type ofdevice that can be used for detecting hazards occurring within astructure, e.g., a home, an office or another structure. However, thissmart hazard detector may also be capable of controlling other devices,detecting non-hazard related events (e.g., security related events),and/or working in cooperation with other devices to provide additionalfeatures to the smart-home environment. Again, it is within the scope ofthe present teachings for embodiments of the smart hazard detectors ofthe present invention to detect measurable characteristics other thanhazards (e.g., pressure, flow rate, height, position, velocity,acceleration, capacity, power, temperatures, loudness, and brightness)and monitor and/or respond to one or more measurable characteristics ofone or more physical systems.

It is to be appreciated that “smart-home environments” may refer tosmart environments for homes such as a single-family house, but thescope of the present teachings is not so limited, the present teachingsbeing likewise applicable, without limitation, to duplexes, townhomes,multi-unit apartment buildings, hotels, retail stores, office buildings,industrial buildings, and more generally any living space or work spacehaving one or more smart hazard detectors.

It is to be further appreciated that while the terms user, customer,installer, homeowner, occupant, guest, tenant, landlord, repair person,and the like may be used to refer to the person or persons who areinteracting with the smart hazard detector or user interface in thecontext of some particularly advantageous situations described herein,these references are by no means to be considered as limiting the scopeof the present teachings with respect to the person or persons who areperforming such actions. Thus, for example, the terms user, customer,purchaser, installer, subscriber, and homeowner may often refer to thesame person in the case of a single-family residential dwelling, becausethe head of the household is often the person who makes the purchasingdecision, buys the unit, and installs and configures the unit, and isalso one of the users of the unit. However, in other scenarios, such asa landlord-tenant environment, the customer may be the landlord withrespect to purchasing the unit, the installer may be a local apartmentsupervisor, a first user may be the tenant, and a second user may againbe the landlord with respect to remote control functionality.Importantly, while the identity of the person performing the action maybe germane to a particular advantage provided by one or more of theembodiments—for example, the password-protected hazard detectionfunctionality described further herein may be particularly advantageouswhere the landlord holds the sole password and can control hazarddetection via the hazard detection device—such identity should not beconstrued in the descriptions that follow as necessarily limiting thescope of the present teachings to those particular individuals havingthose particular identities.

Turning to the figures, FIG. 1 illustrates an example of a smart-homeenvironment 100 within which one or more of the devices, methods,systems, services, and/or computer program products described furtherherein can be applicable. The depicted smart-home environment 100includes a structure 150, which can include, e.g., a house, officebuilding, garage, or mobile home. It will be appreciated that devicescan also be integrated into a smart-home environment 100 that does notinclude an entire structure 150, such as an apartment, condominium, oroffice space. Further, the smart-home environment can control and/or becoupled to devices outside of the actual structure 150. Indeed, severaldevices in the smart-home environment need not physically be within thestructure 150 at all. For example, a device controlling a pool heater orirrigation system 116 can be located outside of the structure.

The depicted structure 150 includes a plurality of rooms 152, separatedat least partly from each other via walls 154. The walls 154 can includeinterior walls or exterior walls. Each room can further include a floor156 and a ceiling 158. Devices can be mounted on, integrated with and/orsupported by a wall 154, floor 156 or ceiling 158.

In some embodiments, the smart-home environment 100 of FIG. 1 includes aplurality of devices, including intelligent, multi-sensing,network-connected devices (sometimes referred to herein as “smartdevices”) that can integrate seamlessly with each other and/or with acentral server or a cloud-computing system to provide any of a varietyof useful smart-home objectives, including hazard-detection objectives.The smart-home environment 100 may include one or more intelligent,multi-sensing, network-connected thermostats 102 (hereinafter referredto as “smart thermostats 102”), one or more intelligent,network-connected, multi-sensing hazard detection units 104 (hereinafterreferred to as “smart hazard detectors 104”), and one or moreintelligent, multi-sensing, network-connected entryway interface devices106 (hereinafter referred to as “smart doorbells 106”). Thermostats 102,hazard detectors 104, doorbells 106 are all examples of smart devices.

According to embodiments, the smart thermostat 102 detects ambientclimate characteristics (e.g., temperature and/or humidity) and controlsa climate control system or HVAC system 103 accordingly, such as byturning on and/or off a fan and/or a heat source of the climate controlsystem 103. (In the present disclosure, “climate control system” is usedinterchangeably with “HVAC system,” to clarify that the disclosureapplies equally to systems that do not necessarily include airconditioning. Use of the term “HVAC” herein does not exclude systemsthat lack air conditioning.)

When the fan of the HVAC or climate control system 103 is on, the fanoperates to circulate air between the rooms 152 of the structure 150,and to exhaust air from the structure 150 and draw fresh, outside airinto the structure 150. The smart hazard detector 104 may detect thepresence of a hazardous condition or a substance indicative of ahazardous condition (e.g., smoke, fire, heat, carbon monoxide, etc.).The smart doorbell 106 may detect a person's approach to or departurefrom a location (e.g., an outer door), control doorbell functionality,announce a person's approach or departure via audio or visual means, orcontrol settings on a security system (e.g., to activate or deactivatethe security system when occupants go and come).

In some embodiments, the smart-home environment 100 of FIG. 1 furtherincludes one or more intelligent, multi-sensing, network-connected wallswitches 108 (hereinafter referred to as “smart wall switches 108”),along with one or more intelligent, multi-sensing, network-connectedwall plug interfaces 110 (hereinafter referred to as “smart wall plugs110”). The smart wall switches 108 may detect ambient lightingconditions, detect room-occupancy states, and control a power and/or dimstate of one or more lights. In some instances, smart wall switches 108may also control a power state or speed of a fan, such as a ceiling fan.The smart wall plugs 110 may detect occupancy of a room or enclosure andcontrol supply of power to one or more wall plugs (e.g., such that poweris not supplied to the plug if nobody is home).

Still further, in some embodiments, the smart-home environment 100 ofFIG. 1 includes a plurality of intelligent, multi-sensing,network-connected appliances 112 (hereinafter referred to as “smartappliances 112”), such as refrigerators, stoves and/or ovens,televisions, washers, dryers, lights, stereos, intercom systems,garage-door openers, floor fans, ceiling fans, wall air conditioners,pool heaters, irrigation systems, security systems, and so forth.According to embodiments, the network-connected appliances 112 are madecompatible with the smart-home environment by cooperating with therespective manufacturers of the appliances. For example, the appliancescan be space heaters, window AC units, motorized duct vents, etc. Whenplugged in, an appliance can announce itself to the smart-home network,such as by indicating what type of appliance it is, and it canautomatically integrate with the controls of the smart-home. Suchcommunication by the appliance to the smart home can be facilitated byany wired or wireless communication protocols known by those havingordinary skill in the art. The smart home also can include a variety ofnon-communicating legacy appliances 140, such as old conventionalwasher/dryers, refrigerators, and the like which can be controlled,albeit coarsely (ON/OFF), by virtue of the smart wall plugs 110. Thesmart-home environment 100 can further include a variety of partiallycommunicating legacy appliances 142, such as infrared (“IR”) controlledwall air conditioners or other IR-controlled devices, which can becontrolled by IR signals provided by the smart hazard detectors 104 orthe smart wall switches 108.

Modularity of Smart Devices

According to embodiments, the smart thermostats 102, the smart hazarddetectors 104, the smart doorbells 106, the smart wall switches 108, thesmart wall plugs 110, and other devices of the smart-home environment100 are modular and can be incorporated into older and new houses. Forexample, the devices are designed around a modular platform consistingof two basic components: a head unit and a back plate, which is alsoreferred to as a docking station. Multiple configurations of the dockingstation are provided so as to be compatible with any home, such as olderand newer homes. However, all of the docking stations include a standardhead-connection arrangement, such that any head unit can be removablyattached to any docking station. Thus, in some embodiments, the dockingstations are interfaces that serve as physical connections to thestructure and the voltage wiring of the homes, and the interchangeablehead units contain all of the sensors, processors, user interfaces, thebatteries, and other functional components of the devices.

Many different commercial and functional possibilities for provisioning,maintenance, and upgrade are possible. For example, after years of usingany particular head unit, a user will be able to buy a new version ofthe head unit and simply plug it into the old docking station. There arealso many different versions for the head units, such as low-costversions with few features, and then a progression ofincreasingly-capable versions, up to and including extremely fancy headunits with a large number of features. Thus, it should be appreciatedthat the various versions of the head units can all be interchangeable,with any of them working when placed into any docking station. This canadvantageously encourage sharing and re-deployment of old head units—forexample, when an important high-capability head unit, such as a hazarddetector, is replaced by a new version of the head unit, then the oldhead unit can be re-deployed to a backroom or basement, etc. Accordingto embodiments, when first plugged into a docking station, the head unitcan ask the user (by 2D LCD display, 2D/3D holographic projection, voiceinteraction, etc.) a few simple questions such as, “Where am I” and theuser can indicate “living room”, “kitchen” and so forth.

Remote Control of Smart Devices

By virtue of network connectivity, one or more of the smart-home devicesof FIG. 1 can further allow a user to interact with the device even ifthe user is not proximate to the device. For example, a user cancommunicate with a device using a computer (e.g., a desktop computer,laptop computer, or tablet) or other portable electronic device (e.g., asmartphone) 166. Herein, all such smartphones, tables, mobile andstationary computers are referred to as “computer” 166. A webpage or appcan be configured to receive communications from the user and controlthe device based on the communications and/or to present informationabout the device's operation to the user. For example, the user can viewa current setpoint temperature for a device and adjust it using acomputer 166. The user can be in the structure during this remotecommunication, or outside the structure.

As discussed, users can control the smart thermostat and other smartdevices in the smart-home environment 100 using a computer 166, which asnoted above may be a network-connected computer or portable electronicdevice such as a smartphone or tablet. In some examples, some or all ofthe occupants (e.g., individuals who live in the home) can registertheir computer 166 with the smart-home environment 100. Suchregistration can be made at a central server to authenticate theoccupant and/or the device as being associated with the home and to givepermission to the occupant to use the device to control the smartdevices in the home. An occupant can use their registered computer 166to remotely control the smart devices of the home, such as when theoccupant is at work or on vacation. The occupant may also use theirregistered device to control the smart devices when the occupant isactually located inside the home, such as when the occupant is sittingon a couch inside the home. It should be appreciated that instead of orin addition to registering computers 166, the smart-home environment 100makes inferences about which individuals live in the home and aretherefore occupants and which computers 166 are associated with thoseindividuals. As such, the smart-home environment “learns” who is anoccupant and permits the computers 166 associated with those individualsto control the smart devices of the home.

Guest Mode for Thermostat Controls

In some instances, guests desire to control the smart devices. Forexample, the smart-home environment may receive communication from anunregistered mobile device of an individual inside of the home, wheresaid individual is not recognized as an occupant of the home. Further,for example, a smart-home environment may receive communication from amobile device of an individual who is known to be or who is registeredas a guest.

According to embodiments, a guest-layer of controls can be provided toguests of the smart-home environment 100. The guest-layer of controlsgives guests access to basic controls (e.g., a judicially selectedsubset of features of the smart devices), such as temperatureadjustments, but it locks out other functionalities. The guest layer ofcontrols can be thought of as a “safe sandbox” in which guests havelimited controls, but they do not have access to more advanced controlsthat could fundamentally alter, undermine, damage, or otherwise impairthe occupant-desired operation of the smart devices. For example, theguest layer of controls may not permit the guest to adjust a heat-pumplockout temperature. In some embodiments, guests also receive alerts,alarms, and other notifications. For example, in the event that a smarthazard detector 104 detects a hazardous condition, such as a dangerousamount of smoke or carbon monoxide, an alert is sent to devicesassociated with guests, as well as to devices of the registeredoccupants.

A use case example of this is when a guest is in a smart home, the guestcould walk up to the thermostat and turn the dial manually, but theguest may not want to walk around the house “hunting” the thermostat,especially at night while the home is dark and others are sleeping.Further, the guest may not want to go through the hassle of downloadingthe necessary application to their device for remotely controlling thethermostat. In fact, the guest may not have the home owner's logincredentials, etc., and therefore cannot remotely control the thermostatvia such an application. Accordingly, according to embodiments of theinvention, the guest can open a mobile browser on their mobile device,type a keyword, such as “NEST” into the URL field and tap “Go” or“Search”, etc. In response, the device presents the guest with a userinterface, such as Thermozilla UI, which allows the guest to move thetarget temperature between a limited range, such as “65” and “80”. Asdiscussed, the user interface provides a guest layer of controls thatare limited to basic functions. The guest cannot change the targethumidity, modes, or view energy history.

According to embodiments, to enable guests to access the user interfacethat provides the guest layer of controls, a local webserver is providedthat is accessible in the local area network (LAN). It does not requirea password, because physical presence inside the home is establishedreliably enough by the guest's presence on the LAN. In some embodiments,during installation of the smart device, such as the smart thermostat,the home owner is asked if they want to enable a Local Web App (LWA) onthe smart device. Business owners will likely say no; home owners willlikely say yes. When the LWA option is selected, the smart devicebroadcasts to the LAN that the above referenced keyword, such as “NEST”,is now a host alias for its local web server. Thus, no matter whose homea guest goes to, that same keyword (e.g., “NEST”) is always the URL youuse to access the LWA, provided the smart device is purchased from thesame manufacturer. Further, according to embodiments, if there is morethan one smart device on the LAN, the second and subsequent smartdevices do not offer to set up another LWA. Instead, they registerthemselves as target candidates with the master LWA. And in this casethe LWA user would be asked which smart device they want to change thetemperature on before getting the simplified user interface, such asThermozilla UI, for the particular smart device they choose.

According to embodiments, a guest layer of controls may also be providedto users by means other than a computer 166. For example, the smartdevice, such as the smart thermostat, may be equipped withwalkup-identification technology (e.g., face recognition, RFID,ultrasonic sensors) that “fingerprints” or creates a “signature” for theoccupants of the home. The walkup-identification technology can be thesame as or similar to the fingerprinting and signature creatingtechniques descripted in other sections of this application. Inoperation, when a person who does not live in the home or is otherwisenot registered with the smart home or whose fingerprint or signature isnot recognized by the smart home “walks up” to a smart device, the smartdevice provides the guest with the guest layer of controls, rather thanfull controls.

As described below, the smart thermostat and other smart devices “learn”by observing occupant behavior. For example, the smart thermostat learnsoccupants' preferred temperature set-points for mornings and evenings,and it learns when the occupants are asleep or awake, as well as whenthe occupants are typically away or at home, for example. According toembodiments, when a guest controls the smart devices, such as the smartthermostat, the smart devices do not “learn” from the guest. Thisprevents the guest's adjustments and controls from affecting the learnedpreferences of the occupants.

Smart Tv Remote Control

According to some embodiments, a smart television remote control isprovided. The smart remote control recognizes occupants by thumbprint,visual identification, RFID, etc., and it recognizes a user as a guestor as someone belonging to a particular class having limited control andaccess (e.g., child). Upon recognizing the user as a guest or someonebelonging to a limited class, the smart remote control only permits thatuser to view a subset of channels and to make limited adjustments to thesettings of the television and other devices. For example, a guestcannot adjust the digital video recorder (DVR) settings, and a child islimited to viewing child-appropriate programming.

According to some embodiments, similar controls are provided for otherinstruments, utilities, and devices in the house. For example, sinks,bathtubs, and showers may be controlled by smart spigots that recognizeusers as guests or as children, and therefore prevent water fromexceeding a designated temperature.

Mesh Network of Spokesman and Low-Powered Nodes

In some embodiments, in addition to containing processing and sensingcapabilities, each of the devices 102, 104, 106, 108, 110, 112, 114, and116 (and other devices with such capabilities, which may be collectivelyreferred to herein as “smart devices”) is capable of data communicationsand information sharing with any other of the smart devices, as well asto any central server or cloud-computing system or any other device thatis network-connected anywhere in the world. The required datacommunications can be carried out using any of a variety of custom orstandard wireless protocols (Wi-Fi, ZigBee, 6LoWPAN, etc.) and/or any ofa variety of custom or standard wired protocols (CAT6 Ethernet,HomePlug, etc.)

According to embodiments, all or some of the smart devices can serve aswireless or wired repeaters. For example, a first one of the smartdevices can communicate with a second one of the smart device via awireless router 160. The smart devices can further communicate with eachother via a connection to a network, such as the Internet 162. Throughthe Internet 162, the smart devices can communicate with a centralserver or a cloud-computing system 164. The central server orcloud-computing system 164 can be associated with a manufacturer,support entity, or service provider associated with the device. For oneembodiment, a user may be able to contact customer support using adevice itself rather than needing to use other communication means suchas a telephone or Internet-connected computer. Certain embodiments cantransmit data such as measurements of temperature, light, smoke, CO,sound, motion, control settings, alarm status, actions performed by thesmart devices, and the like to cloud-computing system 164 for offlineanalysis. Further, software updates can be automatically sent from thecentral server or cloud-computing system 164 to devices (e.g., whenavailable, when purchased, or at routine intervals).

According to embodiments, the smart devices combine to create a meshnetwork of spokesman and low-power nodes in the smart-home environment100, where some of the smart devices are “spokesman” nodes and othersare “low-powered” nodes. Some of the smart devices in the smart-homeenvironment 100 are battery powered, while others have a regular andreliable power source, such as by connecting to wiring (e.g., to 120Vline voltage wires) behind the walls 154 of the smart-home environment.The smart devices that have a regular and reliable power source arereferred to as “spokesman” nodes. These nodes are equipped with thecapability of using any wireless protocol or manner to facilitatebidirectional communication with any of a variety of other devices inthe smart-home environment 100 as well as with the central server orcloud-computing system 164. On the other hand, the devices that arebattery powered are referred to as “low-power” nodes. These nodes tendto be smaller than spokesman nodes and can only communicate usingwireless protocols that requires very little power, such as Zigbee,6LoWPAN, etc. Further, some, but not all, low-power nodes are incapableof bidirectional communication. These low-power nodes send messages, butthey are unable to “listen”. Thus, other devices in the smart-homeenvironment 100, such as the spokesman nodes, cannot send information tothese low-power nodes.

As described, the smart devices serve as low-power and spokesman nodesto create a mesh network in the smart-home environment 100. Individuallow-power nodes in the smart-home environment regularly send outmessages regarding what they are sensing, and the other low-powerednodes in the smart-home environment—in addition to sending out their ownmessages—repeat the messages, thereby causing the messages to travelfrom node to node (i.e., device to device) throughout the smart-homeenvironment 100. The spokesman nodes in the smart-home environment 100are able to “drop down” to low-powered communication protocols toreceive these messages, translate the messages to other communicationprotocols, and send the translated messages to other spokesman nodesand/or the central server or cloud-computing system 164. Thus, thelow-powered nodes using low-power communication protocols are able sendmessages across the entire smart-home environment 100 as well as overthe Internet 162 to the central server or cloud-computing system 164.According to embodiments, the mesh network enables the central server orcloud-computing system 164 regularly receive data from all of the smartdevices in the home, make inferences based on the data, and sendcommands back to one of the smart devices to accomplish some of thesmart-home objectives descried herein.

As described, the spokesman nodes and some of the low-powered nodes arecapable of “listening”. Accordingly, users, other devices, and thecentral server or cloud-computing system 164 can communicate controls tothe low-powered nodes. For example, a user can use a computer 166 (e.g.,a smartphone or other portable electronic device) to send commands overthe Internet to the central server or cloud-computing system 164, whichthen relays the commands to the spokesman nodes in the smart-homeenvironment 100. The spokesman nodes drop down to a low-power protocolto communicate the commands to the low-power nodes throughout thesmart-home environment, as well as to other spokesman nodes that did notreceive the commands directly from the central server or cloud-computingsystem 164.

Smart Nightlight

An example of a low-power node is a smart nightlight 170. In addition tohousing a light source, the smart nightlight 170 houses an occupancysensor, such as an ultrasonic or passive IR sensor, and an ambient lightsensor, such as a photoresistor or a single-pixel sensor that measureslight in the room. In some embodiments, the smart nightlight 170 isconfigured to activate the light source when its ambient light sensordetects that the room is dark and when its occupancy sensor detects thatsomeone is in the room. In other embodiments, the smart nightlight 170is simply configured to activate the light source when its ambient lightsensor detects that the room is dark. Further, according to embodiments,the smart nightlight 170 includes a low-power wireless communicationchip (e.g., ZigBee chip) that regularly sends out messages regarding theoccupancy of the room and the amount of light in the room, includinginstantaneous messages coincident with the occupancy sensor detectingthe presence of a person in the room. As mentioned above, these messagesmay be sent wirelessly, using the mesh network, from node to node (i.e.,smart device to smart device) within the smart-home environment 100 aswell as over the Internet 162 to the central server or cloud-computingsystem 164.

Example Spokesman and Low-Powered Nodes and Uses of Those Nodes in theMesh Network

Other examples of low-powered nodes include battery-powered versions ofthe smart hazard detectors 104. These smart hazard detectors 104 areoften located in an area without access to constant and reliable powerand, as discussed in detail below, may include any number and type ofsensors, such as smoke/fire/heat sensors, carbon monoxide/dioxidesensors, occupancy/motion sensors, ambient light sensors, temperaturesensors, humidity sensors, and the like. Furthermore, smart hazarddetectors 104 can send messages that correspond to each of therespective sensors to the other devices and the central server orcloud-computing system 164, such as by using the mesh network asdescribed above.

Examples of spokesman nodes include smart doorbells 106, smartthermostats 102, wired versions of smart hazard detectors 104, smartwall switches 108, and smart wall plugs 110. These devices 102, 104,106, 108, and 110 are often located near and connected to a reliablepower source, and therefore can include more power-consuming components,such as one or more communication chips capable of bidirectionalcommunication in any variety of protocols.

Alarm Repeaters

In some embodiments, these low-powered and spokesman nodes (e.g.,devices 102, 104, 106, 108, 110, 112, and 170) can function as “alarmbroadcasters” for a hazard-detection system in the smart-homeenvironment. For example, in the even a smart hazard detector 104detects a hazardous condition, such dangerous amounts of smoke or carbonmonoxide, the smart hazard detector 104 sends an alarm message to thecentral server or cloud-computing system 164, which instructs the othersmart devices in the smart-home environment 100 to provide an alarm,alerting occupants to the dangerous condition. Thus, thehazard-detection system could be enhanced by various low-powered andspokesman nodes located throughout the smart-home environment 100, allcapable of providing audible or visual alerts. In this example, a usercould enhance the safety of the smart-home environment 100 by buying andinstalling extra smart devices capable of alerting occupants ofadditional rooms to dangerous conditions.

Lights “Follow” User Through House

In some embodiments, the mesh network can be used to automatically turnon and off lights as a person transitions from room to room. Forexample, the low-powered and spokesman nodes (e.g., devices 102, 104,106, 108, 110, 112, and 170) detect the person's movement through thesmart-home environment and communicate corresponding messages throughthe mesh network. Using the messages that indicate which rooms areoccupied, the central server or cloud-computing system 164 or some otherdevice activates and deactivates the smart wall switches 108 toautomatically provide light as the person moves from room to room in thesmart-home environment 100. Further, users may provide pre-configurationinformation that indicates which smart wall plugs 110 provide power tolamps and other light sources, such as the smart nightlight 170.Alternatively, this mapping of light sources to wall plugs 110 can bedone automatically (e.g., the smart wall plugs 110 detect when a lightsource is plugged into it, and it sends a corresponding message to thecentral server or cloud-computing system 164). Using this mappinginformation in combination with messages that indicate which rooms areoccupied, the central server or cloud-computing system 164 or some otherdevice activates and deactivates the smart wall plugs 110 that providepower to lamps and other light sources so as to track the person'smovement and provide light as the person moves from room to room.

Emergency Exit Lighting

In some embodiments, the mesh network of low-powered and spokesman nodescan be used to provide exit lighting in the event of an emergency. Insome instances, to facilitate this, users provide pre-configurationinformation that indicates exit routes in the smart-home environment100. For example, for each room in the house, the user provides a map ofthe best exit route. It should be appreciated that instead of a userproviding this information, the central server or cloud-computing system164 or some other device could automatically determine the routes usinguploaded maps, diagrams, architectural drawings of the smart-home house,as well as using a map generated based on positional informationobtained from the nodes of the mesh network (e.g., positionalinformation from the devices is used to construct a map of the house).In operation, when an alarm is activated (e.g., when one or more of thesmart hazard detector 104 detects smoke and activates an alarm), thecentral server or cloud-computing system 164 or some other device usesoccupancy information obtained from the low-powered and spokesman nodesto determine which rooms are occupied and then turns on lights (e.g.,nightlights 170, wall switches 108, wall plugs 110 that power lamps,etc.) along the exit routes from the occupied rooms so as to provideemergency exit lighting.

HVAC Control Algorithms that Follow Occupants and Adjust Accordingly

In many homes, the HVAC or climate control system heats and/or coolssome rooms or zones more efficiently than others, thereby causingtemperature variations throughout the home. For example, during aheating cycle, the more efficient rooms and zones are heated to warmertemperature than the less efficient rooms or zones. To compensate fordisparate temperatures across rooms and zones, users commonly have tomanually adjust the temperature setting of the thermostat differentlydepending on which room or zone in the home the user is currentlyoccupying. For example, in a home where the upstairs is more efficientlyheated than the downstairs and where the thermostat is located upstairs,the user has to set the temperature of the upstairs thermostat higherthan the desired temperature in order to heat the downstairs to thedesired temperature. In this example, to achieve a downstairstemperature of 70° F., the user may have to set the upstairs thermostatto 73° F.

Rather than the user having to manually adjust the thermostat asdescribed above, embodiments of the smart thermostats 102 are furtherenhanced by logical integration with other low-powered and spokesmannodes in the home according to rules-based inferencing techniques orartificial intelligence techniques for automatically detecting userlocation in the home and adjusting the thermostat settings accordingly.With reference to the example above, embodiments of the invention detectthat the users are downstairs and automatically adjust the upstairsthermostat so as to achieve the desired temperature of 70° F.downstairs.

To accomplish this, according to embodiments, the occupancy- andtemperature-sensing capabilities of the smart thermostats 102 are usedto track occupant location as well as room and zone temperatures. Inthese embodiments, the temperature readings from the smart thermostat102 closest to the occupants' current locations are weighted heaviest.Thus, the smart thermostats 102 will control the HVAC system to heat orcool the locations nearest the occupants to the user-selectedtemperature, even if this causes other locations in the home to beheated or cooled to temperatures above or below the user-selectedtemperature. However, embodiments where smart thermostats 102 alone areused to determine occupant location and room and zone temperatures havelimited effectiveness in homes that have only a few smart thermostats102. For example, these embodiments may not be effective in a two-storyhome with only one smart thermostat 102 because the smart thermostat 102can only determine occupancy and temperature in the room or zone inwhich it is installed.

As such, according to some embodiments, occupancy and temperature dataobtained from other low-powered and spokesman nodes (e.g., devices 104,106, 108, 110, 112, and 170), which are often located in many roomsthroughout many homes, is used to supplement the occupancy andtemperature data obtained by the limited number of smart thermostats 102often found in home. This enables the smart-home environment 100 to moreaccurately determine which rooms of the smart home are occupied and toaccurately determine the temperature of those rooms at any given time.Upon determining which rooms are occupied, the temperature readings fromthose rooms are more heavily weighted than the temperature readings fromunoccupied rooms when controlling the HVAC system.

An example will now be provided for illustrative purposes. In thisexample, the smart-home environment 100 includes only one smartthermostat 102 but it also includes multiple smart hazard detectors 104.In this example, no other types of low-powered or spokesman nodes (e.g.,devices 106, 108, 110, 112, and 170) are provided in the house. If anoccupant is in a room that includes the smart thermostat 102 as well asone of the smart hazard detectors 104, then the temperature reading ofthe thermostat 102 is weighted the most when determining the temperatureof the room. This is in part because the smart thermostat 102 is mountedabout five feet from floor, whereas the smart hazard detectors 104 areoften mounted on or close to the ceiling, where temperature is differentthan what occupants actually experience. On the other hand, if theoccupant is located in a room that does not have the smart thermostat102 but it does have one of the smart hazard detectors 104, then thetemperature reading of the smart hazard detector 104 is weighted themost. It should be appreciated that instead of or in addition to thesmart hazard detectors 104, the home can include other types oflow-powered and spokesman nodes (e.g., devices 106, 108, 110, 112, and170) for gathering occupancy and temperature data for the various roomsof the home.

Using occupancy and temperature data obtained through the mesh networkfrom multiple low-powered and spokesman nodes to adjust HVAC settingscan reduce cost and environmental impact, while enhancing occupantcomfort. For example, temperature readings from devices located in roomsof the home that are rarely occupied, such as guest rooms, can belargely ignored when the rooms are unoccupied, thereby avoiding thecosts and environmental impact of heating and cooling and unoccupiedroom. However, when the room is occupied, the smart-home environment 100will account for the temperature readings from the room when controllingthe HVAC system, so as to make the occupant of the room comfortable.

In operation, responsive to receiving a desired temperature setting froma user, the smart thermostat 102 controls the HVAC or climate controlsystem so as to achieve the desired temperature in the occupied rooms.To do so, the smart thermostat 102 heats or cools the home so that aweighted average temperature of the home equals the desired temperature.The weighted average temperature is the average temperature of the roomsof the home, where temperature data from occupied rooms is more heavilyweighted than temperature data from unoccupied rooms. The more heavilyweighted the temperature data from occupied rooms, the more likely thetemperature in those rooms matches the desired temperature.

Quiet Time

In many homes, the HVAC system (e.g., hot water, steam, forced air, AC,humidifiers, etc.) are noisy, especially during “transitions”, such asshifting from off to on. This noisiness is particularly noticeable whenthe home is quiet, such as at night when the occupants are sleeping.Accordingly, the smart thermostats 102, according to some embodiments,are configured to minimize HVAC “transitions” when the home is quiet,and especially when occupants are determined to be sleeping. The ideahere is that when the home is quiet (e.g., everyone is sleeping), theHVAC system is also quiet. This feature is sometimes referred to hereinas “Quiet Time”.

According to embodiments, upon sensing that the home is quiet, smartthermostat 102 controls the HVAC system so as to make as little noise aspossible. To sense when the home is quiet, according to embodiments, thesmart thermostats 102 leverage noise data received from noise sensors ofthe other smart devices located in the mesh network of the smart-homeenvironment. When the noise level is low, such as below a predeterminednoise threshold, the smart thermostat 102 enters a “quiet time” mode,where it “relaxes” the deadband range around the set temperature.Deadband range is the temperature range where the HVAC system is offbecause the temperature is close enough to the set temperature. Forexample, if the set temperature is 70 F and the deadband range is 68-72F, then the heat turns on if temperature drops below 68 F, the AC turnson if temperature rises above 72 F, but neither are on when thetemperature is in the deadband range of 68-72 F. “Relaxing” the deadbandrange makes the range bigger. For example, during “quiet time”, thedeadband range of 68-72 F could be relaxed to 65-75 F. Thus, the HVACsystem will not turn on and off as often.

It should also be appreciated that, in addition to or instead of usingnoise sensor to determine when the home is “quiet”, the smart thermostat102 can also leverage the motion detection capabilities of the smartdevices in the home. For example, motion tends to be associated withnoise. Accordingly, when no motion is detected in the home for a period,the smart thermostat 102 can infer that there is no noise in the homeand evoke “quiet time”.

Further, according to embodiments, the smart thermostats 102 enter“quiet time” mode upon determining that an occupant of the home aresleeping. According to embodiments, to determine that occupants aresleeping, smart-home environment 100 leverages the sensors of the smartdevices located in the mesh network of the smart-home environment incombination with rules-based inference engines or artificialintelligence provided at the central server or cloud-computing system164. According to embodiments, the smart devices in the smart-homeenvironment 100 that happens to be closest to an occupant when thatoccupant falls asleep transmit a message indicating that the occupanthas stopped moving and appears to be sleeping. The message will betransmitted through the mesh network to the smart thermostats 102, whichwill then enter “quiet time” mode.

Further, according to embodiments, the smart thermostat 102 enters“quiet time” mode according to a schedule, such as between 11:00 PM and6:00 AM. According to other embodiments, if an occupant wakes in themiddle of the night to visit the restroom, the smart thermostat 102receives information that there is movement in the home and, if thetemperature is near the outer limits of the deadband range, thethermostat 102 transitions the HVAC cycle while the occupant is likelystill awake.

Enhancing Auto-Away

According to embodiments, occupancy data obtained from the variouslow-powered and spokesman nodes located throughout the smart-homeenvironment 100 is used to determine when the house is unoccupied and,upon determining that the house is unoccupied, the smart-homeenvironment 100 automatically turns off or reduces operation of the HVACsystem to conserve energy and lessen environmental impact. This featureis sometimes referred to herein as “auto away”. In some examples, thesmart-home environment 100 determines that the home is unoccupied uponreceiving no occupancy data from the low-powered and spokesman nodes inthe home for the duration of a period of time, such as one hour. Inother words, if none of the low-powered or spokesman nodes detects anymovement in the home during daytime hours for the duration of theperiod, then the smart-home environment 100 makes an inference that thehome is unoccupied and invokes “auto away” to turn off or reduceoperation of the HVAC system. User dissatisfaction may occur ininstances where the smart-home environment 100 incorrectly infers thatthe home is unoccupied and improperly invokes “auto away”, therebyturning of the HVAC system and allowing the home to rise or fall touncomfortable temperatures. Accordingly, it is desirable to havealgorithms for preventing the smart-home environment 100 from improperlyinvoking “auto away”.

One such algorithm involves learning which routes an occupant takes whenexiting the home, and not invoking “auto away” unless the occupant takesone of the learned routes. For example, the smart-home environment 100can learn that the occupant walks through a particular hallway each timethey leave the home. Thus, in an example case, when it is daytime duringa weekday when the occupant is typically at work, and even though thereis no movement in the house which makes it seem like the house isunoccupied, the smart-home environment 100 nonetheless make an inferencethat the house is occupied because the occupant did not walk through theparticular hallway. In such an example, the occupant could be sick andstill in bed. Accordingly, the smart-home environment 100 does notinvoke “auto away” and it permits the HVAC system to function normally.

Robots

Further included and illustrated in the exemplary smart-home environment100 of FIG. 1 are service robots 165 each configured to carry out, in anautonomous manner, any of a variety of household tasks. For someembodiments, the service robots 165 can be respectively configured toperform floor sweeping, floor washing, etc. in a manner similar to thatof known commercially available devices such as the ROOMBA™ and SCOOBA™products sold by iRobot, Inc. of Bedford, Mass. Tasks such as floorsweeping and floor washing can be considered as “away” or “while-away”tasks for purposes of the instant description, as it is generally moredesirable for these tasks to be performed when the occupants are notpresent. For other embodiments, one or more of the service robots 165are configured to perform tasks such as playing music for an occupant,serving as a localized thermostat for an occupant, serving as alocalized air monitor/purifier for an occupant, serving as a localizedbaby monitor, serving as a localized hazard detector for an occupant,and so forth, it being generally more desirable for such tasks to becarried out in the immediate presence of the human occupant. Forpurposes of the instant description, such tasks can be considered as“human-facing” or “human-centric” tasks.

When serving as a localized thermostat for an occupant, a particular oneof the service robots 165 can be considered to be facilitating what canbe called a “personal comfort-area network” for the occupant, with theobjective being to keep the occupant's immediate space at a comfortabletemperature wherever that occupant may be located in the home. This canbe contrasted with conventional wall-mounted room thermostats, whichhave the more attenuated objective of keeping a statically-definedstructural space at a comfortable temperature. According to oneembodiment, the localized-thermostat service robot 165 is configured tomove itself into the immediate presence (e.g., within five feet) of aparticular occupant who has settled into a particular location in thehome (e.g. in the dining room to eat their breakfast and read the news).The localized-thermostat service robot 165 includes a temperaturesensor, a processor, and wireless communication components configuredsuch that control communications with the HVAC system, either directlyor through a wall-mounted wirelessly communicating thermostat coupled tothe HVAC system, are maintained and such that the temperature in theimmediate vicinity of the occupant is maintained at their desired level.If the occupant then moves and settles into another location (e.g. tothe living room couch to watch television), the localized-thermostatservice robot 165 proceeds to move and park itself next to the couch andkeep that particular immediate space at a comfortable temperature.

Technologies by which the localized-thermostat service robot 165 (and/orthe larger smart-home system of FIG. 1) can identify and locate theoccupant whose personal-area space is to be kept at a comfortabletemperature can include, but are not limited to, RFID sensing (e.g.,person having an RFID bracelet, RFID necklace, or RFID key fob),synthetic vision techniques (e.g., video cameras and face recognitionprocessors), audio techniques (e.g., voice, sound pattern, vibrationpattern recognition), ultrasound sensing/imaging techniques, andinfrared or near-field communication (NFC) techniques (e.g., personwearing an infrared or NFC-capable smartphone), along with rules-basedinference engines or artificial intelligence techniques that draw usefulconclusions from the sensed information (e.g., if there is only a singleoccupant present in the home, then that is the person whose immediatespace should be kept at a comfortable temperature, and the selection ofthe desired comfortable temperature should correspond to that occupant'sparticular stored profile).

When serving as a localized air monitor/purifier for an occupant, aparticular service robot 165 can be considered to be facilitating whatcan be called a “personal health-area network” for the occupant, withthe objective being to keep the air quality in the occupant's immediatespace at healthy levels. Alternatively or in conjunction therewith,other health-related functions can be provided, such as monitoring thetemperature or heart rate of the occupant (e.g., using finely remotesensors, near-field communication with on-person monitors, etc.). Whenserving as a localized hazard detector for an occupant, a particularservice robot 165 can be considered to be facilitate what can be calleda “personal safety-area network” for the occupant, with the objectivebeing to ensure there is no excessive carbon monoxide, smoke, fire,etc., in the immediate space of the occupant. Methods analogous to thosedescribed above for personal comfort-area networks in terms of occupantidentifying and tracking are likewise applicable for personalhealth-area network and personal safety-area network embodiments.

According to some embodiments, the above-referenced facilitation ofpersonal comfort-area networks, personal health-area networks, personalsafety-area networks, and/or other such human-facing functionalities ofthe service robots 165, are further enhanced by logical integration withother smart sensors in the home according to rules-based inferencingtechniques or artificial intelligence techniques for achieving betterperformance of those human-facing functionalities and/or for achievingthose goals in energy-conserving or other resource-conserving ways.Thus, for one embodiment relating to personal health-area networks, theair monitor/purifier service robot 165 can be configured to detectwhether a household pet is moving toward the currently settled locationof the occupant (e.g., using on-board sensors and/or by datacommunications with other smart-home sensors along with rules-basedinferencing/artificial intelligence techniques), and if so, the airpurifying rate is immediately increased in preparation for the arrivalof more airborne pet dander. For another embodiment relating to personalsafety-area networks, the hazard detector service robot 165 can beadvised by other smart-home sensors that temperature and humidity levelsare rising in the kitchen, which is nearby to the occupant's currentdining room location, and responsive to this advisory the hazarddetector service robot 165 may temporarily raise a pre-hazard detectionthreshold, such as a smoke detection pre-hazard threshold, under aninference that any small increases in ambient smoke levels will mostlikely be due to cooking activity and not due to a genuinely hazardouscondition.

The above-described “human-facing” and “away” functionalities can beprovided, without limitation, by multiple distinct service robots 165having respective dedicated ones of such functionalities, by a singleservice robot 165 having an integration of two or more different ones ofsuch functionalities, and/or any combinations thereof (including theability for a single service robot 165 to have both “away” and “humanfacing” functionalities) without departing from the scope of the presentteachings. Electrical power can be provided by virtue of rechargeablebatteries or other rechargeable methods, with FIG. 1 illustrating anexemplary out-of-the-way docking station 164 to which the service robots165 will automatically dock and recharge its batteries (if needed)during periods of inactivity. Each service robot 165 may includewireless communication components that facilitate data communicationswith one or more of the other wirelessly communicating smart-homesensors of FIG. 1 and/or with one or more other service robots 165(e.g., using Wi-Fi, Zigbee, Z-Wave, 6LoWPAN, etc.), and one or more ofthe smart-home devices of FIG. 1 can be in communication with a remoteserver over the Internet. Alternatively or in conjunction therewith,each service robot 165 can be configured to communicate directly with aremote server by virtue of cellular telephone communications, satellitecommunications, 3G/4G network data communications, or other directcommunication method.

Provided according to some embodiments are systems and methods relatingto the integration of the service robot(s) 165 with home securitysensors and related functionalities of the smart-home system. Theembodiments are particularly applicable and advantageous when appliedfor those service robots 165 that perform “away” functionalities or thatotherwise are desirable to be active when the home is unoccupied(hereinafter “away-service robots”). Included in the embodiments aremethods and systems for ensuring that home security systems, intrusiondetection systems, and/or occupancy-sensitive environmental controlsystems (for example, occupancy-sensitive automated setback thermostatsthat enter into a lower-energy-using condition when the home isunoccupied) are not erroneously triggered by the away-service robots.

Provided according to one embodiment is a home automation and securitysystem (e.g., as shown in FIG. 1) that is remotely monitored by amonitoring service by virtue of automated systems (e.g., cloud-basedservers or other central servers, hereinafter “central server”) that arein data communications with one or more network-connected elements ofthe home automation and security system. The away-service robots areconfigured to be in operative data communication with the centralserver, and are configured such that they remain in a non-away-servicestate (e.g., a dormant state at their docking station) unless permissionis granted from the central server (e.g., by virtue of an“away-service-OK” message from the central server) to commence theiraway-service activities. An away-state determination made by the system,which can be arrived at (i) exclusively by local on-premises smartdevice(s) based on occupancy sensor data, (ii) exclusively by thecentral server based on received occupancy sensor data and/or based onreceived proximity-related information such as GPS coordinates from usersmartphones or automobiles, or (iii) any combination of (i) and (ii) canthen trigger the granting of away-service permission to the away-servicerobots by the central server. During the course of the away-servicerobot activity, during which the away-service robots may continuouslydetect and send their in-home location coordinates to the centralserver, the central server can readily filter signals from the occupancysensing devices to distinguish between the away-service robot activityversus any unexpected intrusion activity, thereby avoiding a falseintrusion alarm condition while also ensuring that the home is secure.Alternatively or in conjunction therewith, the central server mayprovide filtering data (such as an expected occupancy-sensing profiletriggered by the away-service robots) to the occupancy sensing nodes orassociated processing nodes of the smart home, such that the filteringis performed at the local level. Although somewhat less secure, it wouldalso be within the scope of the present teachings for the central serverto temporarily disable the occupancy sensing equipment for the durationof the away-service robot activity.

According to another embodiment, functionality similar to that of thecentral server in the above example can be performed by an on-sitecomputing device such as a dedicated server computer, a “master” homeautomation console or panel, or as an adjunct function of one or more ofthe smart-home devices of FIG. 1. In such an embodiment, there would beno dependency on a remote service provider to provide the“away-service-OK” permission to the away-service robots and thefalse-alarm-avoidance filtering service or filter information for thesensed intrusion detection signals.

According to other embodiments, there are provided methods and systemsfor implementing away-service robot functionality while avoiding falsehome security alarms and false occupancy-sensitive environmentalcontrols without the requirement of a single overall event orchestrator.For purposes of the simplicity in the present disclosure, the homesecurity systems and/or occupancy-sensitive environmental controls thatwould be triggered by the motion, noise, vibrations, or otherdisturbances of the away-service robot activity are referenced simply as“activity sensing systems,” and when so triggered will yield a“disturbance-detected” outcome representative of the false trigger (forexample, an alarm message to a security service, or an “arrival”determination for an automated setback thermostat that causes the hometo be heated or cooled to a more comfortable “occupied” setpointtemperature). According to one embodiment, the away-service robots areconfigured to emit a standard ultrasonic sound throughout the course oftheir away-service activity, the activity sensing systems are configuredto detect that standard ultrasonic sound, and the activity sensingsystems are further configured such that no disturbance-detected outcomewill occur for as long as that standard ultrasonic sound is detected.For other embodiments, the away-service robots are configured to emit astandard notification signal throughout the course of their away-serviceactivity, the activity sensing systems are configured to detect thatstandard notification signal, and the activity sensing systems arefurther configured such that no disturbance-detected outcome will occurfor as long as that standard notification signal is detected, whereinthe standard notification signal comprises one or more of: an opticalnotifying signal; an audible notifying signal; an infrared notifyingsignal; an infrasonic notifying signal; a wirelessly transmitted datanotification signal (e.g., an IP broadcast, multicast, or unicastnotification signal, or a notification message sent in an TCP/IP two-waycommunication session).

According to some embodiments, the notification signals sent by theaway-service robots to the activity sensing systems are authenticatedand encrypted such that the notifications cannot be learned andreplicated by a potential burglar. Any of a variety of knownencryption/authentication schemes can be used to ensure such datasecurity including, but not limited to, methods involving third partydata security services or certificate authorities. For some embodiments,a permission request-response model can be used, wherein any particularaway-service robot requests permission from each activity sensing systemin the home when it is ready to perform its away-service tasks, and doesnot initiate such activity until receiving a “yes” or “permissiongranted” message from each activity sensing system (or from a singleactivity sensing system serving as a “spokesman” for all of the activitysensing systems). One advantage of the described embodiments that do notrequire a central event orchestrator is that there can (optionally) bemore of an arms-length relationship between the supplier(s) of the homesecurity/environmental control equipment, on the one hand, and thesupplier(s) of the away-service robot(s), on the other hand, as it isonly required that there is the described standard one-way notificationprotocol or the described standard two-way request/permission protocolto be agreed upon by the respective suppliers.

According to still other embodiments, the activity sensing systems areconfigured to detect sounds, vibrations, RF emissions, or otherdetectable environmental signals or “signatures” that are intrinsicallyassociated with the away-service activity of each away-service robot,and are further configured such that no disturbance-detected outcomewill occur for as long as that particular detectable signal orenvironmental “signature” is detected. By way of example, a particularkind of vacuum-cleaning away-service robot may emit a specific sound orRF signature. For one embodiment, the away-service environmentalsignatures for each of a plurality of known away-service robots arestored in the memory of the activity sensing systems based onempirically collected data, the environmental signatures being suppliedwith the activity sensing systems and periodically updated by a remoteupdate server. For another embodiment, the activity sensing systems canbe placed into a “training mode” for the particular home in which theyare installed, wherein they “listen” and “learn” the particularenvironmental signatures of the away-service robots for that home duringthat training session, and thereafter will suppress disturbance-detectedoutcomes for intervals in which those environmental signatures areheard.

For still another embodiment, which is particularly useful when theactivity sensing system is associated with occupancy-sensitiveenvironmental control equipment rather than a home security system, theactivity sensing system is configured to automatically learn theenvironmental signatures for the away-service robots by virtue ofautomatically performing correlations over time between detectedenvironmental signatures and detected occupancy activity. By way ofexample, for one embodiment an intelligent automatednonoccupancy-triggered setback thermostat such as the Nest LearningThermostat can be configured to constantly monitor for audible and RFactivity as well as to perform infrared-based occupancy detection. Inparticular view of the fact that the environmental signature of theaway-service robot will remain relatively constant from event to event,and in view of the fact that the away-service events will likely either(a) themselves be triggered by some sort of nonoccupancy condition asmeasured by the away-service robots themselves, or (b) occur at regulartimes of day, there will be patterns in the collected data by which theevents themselves will become apparent and for which the environmentalsignatures can be readily learned. Generally speaking, for thisautomatic-learning embodiment in which the environmental signatures ofthe away-service robots are automatically learned without requiring userinteraction, it may be useful for a certain number of false triggers tobe tolerable over the course of the learning process. Accordingly, thisautomatic-learning embodiment may be advantageously applied inoccupancy-sensitive environmental control equipment (such as anautomated setback thermostat) rather than home security systems for thereason that a few false occupancy determinations may cause a fewinstances of unnecessary heating or cooling, but will not otherwise haveany serious consequences, whereas false home security alarms may havemore serious consequences.

Smart Alarm Clock—Detecting when Occupant Falls Asleep

According to embodiments, technologies including the sensors of thesmart devices located in the mesh network of the smart-home environmentin combination with rules-based inference engines or artificialintelligence provided at the central server or cloud-computing system164 are used to provide a personal “smart alarm clock” for individualoccupants of the home. For example, user-occupants can communicate withthe central server or cloud-computing system 164 via their computers 166to access an interface for the smart alarm clock. There, occupants canturn on their “smart alarm clock” and input a wake time for the next dayand/or for additional days. In some embodiments, the occupant may havethe option of setting a specific wake time for each day of the week, aswell as the option of setting some or all of the inputted wake times to“repeat”. Artificial intelligence will be used to consider theoccupant's response to these alarms when they go off and make inferencesabout the user's preferred sleep patterns over time.

According to embodiments, the smart device in the smart-home environment100 that happens to be closest to the occupant when the occupant fallsasleep will be the device that transmits messages regarding when theoccupant stopped moving, from which the central server orcloud-computing system 164 will make inferences about where and when theoccupant prefers to sleep. This closest smart device will as be thedevice that sounds the alarm to wake the occupant. In this manner, the“smart alarm clock” will follow the occupant throughout the house, bytracking the individual occupants based on their “unique signature”,which is determined based on data obtained from sensors located in thesmart devices. For example, the sensors include ultrasonic sensors,passive IR sensors, and the like. The unique signature is based on acombination of walking gate, patterns of movement, voice, height, size,etc. It should be appreciated that facial recognition may also be used.

According to an embodiment, the wake times associated with the “smartalarm clock” are used by the smart thermostat 102 to control the HVAC inan efficient manner so as to pre-heat or cool the house to theoccupant's desired “sleeping” and “awake” temperature settings. Thepreferred settings can be learned over time, such as by observing whichtemperature the occupant sets the thermostat to before going to sleepand which temperature the occupant sets the thermostat to upon wakingup.

According to an embodiment, a device is positioned proximate to theoccupant's bed, such as on an adjacent nightstand, and collects data asthe occupant sleeps using noise sensors, motion sensors (e.g.,ultrasonic, IR, and optical), etc. Data may be obtained by the othersmart devices in the room as well. Such data may include the occupant'sbreathing patterns, heart rate, movement, etc. Inferences are made basedon this data in combination with data that indicates when the occupantactually wakes up. For example, if—on a regular basis—the occupant'sheart rate, breathing, and moving all increase by 5% to 10%, twenty tothirty minutes before the occupant wakes up each morning, thenpredictions can be made regarding when the occupant is going to wake.Other devices in the home can use these predictions to provide othersmart-home objectives, such as adjusting the smart thermostat 102 so asto pre-heat or cool the home to the occupant's desired setting beforethe occupant wakes up. Further, these predictions can be used to set the“smart alarm clock” for the occupant, to turn on lights, etc.

Alzheimer's Disease—Monitor Occupant Movement in Home

According to embodiments, technologies including the sensors of thesmart devices located throughout the smart-home environment incombination with rules-based inference engines or artificialintelligence provided at the central server or cloud-computing system164 are used to detect or monitor the progress of Alzheimer's Disease.For example, the unique signatures of the occupants are used to trackthe individual occupants' movement throughout the smart-home environment100. This data can be aggregated and analyzed to identify patternsindicative of Alzheimer's. Oftentimes, individuals with Alzheimer's havedistinctive patterns of migration in their homes. For example, a personwill walk to the kitchen and stand there for a while, then to the livingroom and stand there for a while, and then back to the kitchen. Thispattern will take about thirty minutes, and then the person will repeatthe pattern. According to embodiments, the remote servers or cloudcomputing architectures 164 analyze the person's migration datacollected by the mesh network of the smart-home environment to identifysuch patterns.

Extensible Devices and Services Platform

FIG. 2 illustrates a network-level view of an extensible devices andservices platform 200 with which a plurality of smart-home environments,such as the smart-home environment 100 of FIG. 1, can be integrated. Theextensible devices and services platform 200 includes remote servers orcloud computing architectures 164. Each of the intelligent,network-connected devices 102, 104, 106, 108, 110, 112, 114, and 116from FIG. 1 (identified simply as “smart devices” herein) cancommunicate with the remote servers or cloud computing architectures164. For example, a connection to the Internet 162 can be establishedeither directly (for example, using 3G/4G connectivity to a wirelesscarrier), through a hubbed network 212 (which can be a scheme rangingfrom a simple wireless router, for example, up to and including anintelligent, dedicated whole-home control node), or through anycombination thereof.

Although in some examples provided herein, the devices and servicesplatform 200 communicates with and collects data from the smart devicesof smart-home environment 100 of FIG. 1, it should be appreciated thatthe devices and services platform 200 communicates with and collectsdata from a plurality of smart-home environments across the world. Forexample, the central server or cloud-computing system 164 can collecthome data 202 from the devices of one or more smart-home environments,where the devices can routinely transmit home data or can transmit homedata in specific instances (e.g., when a device queries the home data202). Thus, the devices and services platform 200 routinely collectsdata from homes across the world. As described, the collected home data202 includes, for example, power consumption data, occupancy data, HVACsettings and usage data, carbon monoxide levels data, carbon dioxidelevels data, volatile organic compounds levels data, sleeping scheduledata, cooking schedule data, inside and outside temperature humiditydata, television viewership data, inside and outside noise level data,etc.

According to embodiments, devices in the home increase their loggingfrequency as they approach a threshold. For example, hazard detector 104increases the frequency at which it samples air and sends correspondingdata to the server 164 as the condition in the home approaches an alarmcondition. For example, upon detecting more than a threshold level ofsmoke, hazard detector 104 samples air at a higher rate and sendscorresponding data to the server 164. In another example, hazarddetector 104 increases the frequency it samples the air for CO upondetecting a threshold level increase in the amount of CO in the home.Further for example, the devices increase logging and sampling frequencyduring “transitions”. For example, upon detecting increased levels ofnoise, light, etc. in a location, a device may switch into a “listening”state where sensors such as passive infrared (hereinafter, “PIR”)sensors, ultrasonic sensors, etc. sample and log (e.g., send data toserver 164) at an increased rate. The increased levels of noise, light,etc. in the location indicates the presence of humans in the room, andthereby indicates that there may be data worth observing in the room.For example, according to embodiments, it may be desirable that thesmart devices be quiet most of the time so as to reduce “chatter” on thenetwork (e.g., reduce frequent updates at the server 164). Thus, if noone is in the room, a smart device may be configured to sample once aminute or once an hour. However, if the smart device senses a“transition” indicating that a person is in the room, then it willsample more often. For example, when the room is occupied, the smartdevice may send to the server 164 temperature data, occupancy data, etc.The server stores this data in home data 202 and runs trend detectingalgorithms against the data. For example, the home data 202 may includelogs and maps of user in-home movements from room to room, time spent ineach room, intra-home occupancy/density maps, etc.

According to embodiments, the home data 202 can be made available tousers so that they can review a log of historical events in the home.For example, they can review the historical CO, smoke, temperature, etc.levels of the various rooms of the home. For example, an examplehistorical log indicates: pre-alarm smoke level detected at 10:14 AM;smoke alarm level detected at 10:26 AM; alarm hushed at 10:31; and smokediminished “everything okay” at 10:50. This enables the user to see thatan alarm condition occurred in the home and how it was resolved. Thehistorical log can also include a history of self-checks executed by thesmart device. For example, it may show a history of time hazarddetectors 104 tested their CO sensors. An example self-check log mayindicated that all hazard detectors in the home self-checked between 1AM and 2 AM, and they are all working properly, including their WiFiconnection is good, their battery level is acceptable, their CO sensoris working properly, etc.

The central server or cloud-computing architecture 164 can furtherprovide one or more services 204. The services 204 can include, e.g.,software updates, customer support, sensor data collection/logging,remote access, remote or distributed control, or use suggestions (e.g.,based on collected home data 202 to improve performance, reduce utilitycost, etc.). Data associated with the services 204 can be stored at thecentral server or cloud-computing system 164 and the central server orthe cloud-computing system 164 can retrieve and transmit the data at anappropriate time (e.g., at regular intervals, upon receiving a requestfrom a user, etc.).

As illustrated in FIG. 2, an embodiment of the extensible devices andservices platform 200 includes a processing engine 206, which can beconcentrated at a single server or distributed among several differentcomputing entities without limitation. The processing engine 206 caninclude engines configured to receive data from devices of smart-homeenvironments (e.g., via the Internet or a hubbed network), to index thedata, to analyze the data and/or to generate statistics based on theanalysis or as part of the analysis. The analyzed data can be stored asderived home data 208.

Results of the analysis or statistics can thereafter be transmitted backto the device that provided home data used to derive the results, toother devices, to a server providing a webpage to a user of the device,or to other non-device entities. For example, use statistics, usestatistics relative to use of other devices, use patterns, and/orstatistics summarizing sensor readings can be generated by theprocessing engine 206 and transmitted. The results or statistics can beprovided via the Internet 162. In this manner, the processing engine 206can be configured and programmed to derive a variety of usefulinformation from the home data 202. A single server can include one ormore engines.

The derived data can be highly beneficial at a variety of differentgranularities for a variety of useful purposes, ranging from explicitprogrammed control of the devices on a per-home, per-neighborhood, orper-region basis (for example, demand-response programs for electricalutilities), to the generation of inferential abstractions that canassist on a per-home basis (for example, an inference can be drawn thatthe homeowner has left for vacation and so security detection equipmentcan be put on heightened sensitivity), to the generation of statisticsand associated inferential abstractions that can be used for governmentor charitable purposes. For example, processing engine 206 can generatestatistics about device usage across a population of devices and sendthe statistics to device users, service providers or other entities(e.g., that have requested or may have provided monetary compensationfor the statistics).

Detection of Sound, Vibration, and/or Motion Created by Running Water

According to some embodiments, sound, vibration, and/or motion sensingcomponents of the smart devices are used to detect sound, vibration,and/or motion created by running water. Based on the detected sound,vibration, and/or motion, the central server or cloud-computingarchitecture 164 makes inferences about water usage in the home andprovides related services. For example, the central server orcloud-computing architecture 164 can run programs/algorithms thatrecognize what water sounds like and when it is running in the home.According to one embodiment, to map the various water sources of thehome, upon detecting running water, the central server orcloud-computing architecture 164 sends a message an occupant's mobiledevice asking if water is currently running or if water has beenrecently run in the home and, if so, which room and whichwater-consumption appliance (e.g., sink, shower, toilet, etc.) was thesource of the water. This enables the central server or cloud-computingarchitecture 164 to determine the “signature” or “fingerprint” of eachwater source in the home. This is sometimes referred to herein as “audiofingerprinting water usage.”

In one illustrative example, the central server or cloud-computingarchitecture 164 creates a signature for the toilet in the masterbathroom, and whenever that toilet is flushed, the central server orcloud-computing architecture 164 will know that the water usage at thattime is associated with that toilet. Thus, the central server orcloud-computing architecture 164 can track the water usage of thattoilet as well as each water-consumption application in the home. Thisinformation can be correlated to water bills or smart water meters so asto provide users with a breakdown of their water usage.

Detection of Sound, Vibration, and/or Motion Created by Mice

According to some embodiments, sound, vibration, and/or motion sensingcomponents of the smart devices are used to detect sound, vibration,and/or motion created by mice and other rodents as well as by termites,cockroaches, and other insects (collectively referred to as “pests”).Based on the detected sound, vibration, and/or motion, the centralserver or cloud-computing architecture 164 makes inferences aboutpest-detection in the home and provides related services. For example,the central server or cloud-computing architecture 164 can runprograms/algorithms that recognize what certain pests sound like, howthey move, and/or the vibration they create, individually and/orcollectively. According to one embodiment, the central server orcloud-computing architecture 164 can determine the “signatures” ofparticular types of pests.

For example, in the event the central server or cloud-computingarchitecture 164 detects sounds that may be associated with pests, itnotifies the occupants of such sounds and suggests hiring a pest controlcompany. If it is confirmed that pests are indeed present, the occupantsinput to the central server or cloud-computing architecture 164 confirmsthat its detection was correct, along with details regarding theidentified pests, such as name, type, description, location, quantity,etc. This enables the central server or cloud-computing architecture 164to “tune” itself for better detection and create “signatures” or“fingerprints” for specific types of pests. For example, the centralserver or cloud-computing architecture 164 can use the tuning as well asthe signatures and fingerprints to detect pests in other homes, such asnearby homes that may be experiencing problems with the same pests.Further, for example, in the event that two or more homes in a“neighborhood” are experiencing problems with the same or similar typesof pests, the central server or cloud-computing architecture 164 canmake inferences that nearby homes may also have such problems or may besusceptible to having such problems, and it can send warning messages tothose homes to help facilitate early detection and prevention.

APIs

In some embodiments, to encourage innovation and research and toincrease products and services available to users, the devices andservices platform 200 expose a range of application programminginterfaces (APIs) 210 to third parties, such as charities 222,governmental entities 224 (e.g., the Food and Drug Administration or theEnvironmental Protection Agency), academic institutions 226 (e.g.,university researchers), businesses 228 (e.g., providing devicewarranties or service to related equipment, targeting advertisementsbased on home data), utility companies 230, and other third parties. TheAPIs 210 are coupled to and permit third-party systems to communicatewith the central server or the cloud-computing system 164, including theservices 204, the processing engine 206, the home data 202, and thederived home data 208. For example, the APIs 210 allow applicationsexecuted by the third parties to initiate specific data processing tasksthat are executed by the central server or the cloud-computing system164, as well as to receive dynamic updates to the home data 202 and thederived home data 208.

For example, third parties can develop programs and/or applications,such as web or mobile apps, that integrate with the central server orthe cloud-computing system 164 to provide services and information tousers. Such programs and application may be, for example, designed tohelp users reduce energy consumption, to preemptively service faultyequipment, to prepare for high service demands, to track past serviceperformance, etc., or to perform any of a variety of beneficialfunctions or tasks now known or hereinafter developed.

According to some embodiments, third-party applications make inferencesfrom the home data 202 and the derived home data 208, such inferencesmay include when are occupants home, when are they sleeping, when arethey cooking, when are they in the den watching television, and when dothey shower. The answers to these questions may help third-partiesbenefit consumers by providing them with interesting information,products and services as well as with providing them with targetedadvertisements.

In one example, a shipping company creates an application that makesinferences regarding when people are at home. The application uses theinferences to schedule deliveries for times when people will most likelybe at home. The application can also build delivery routes around thesescheduled times. This reduces the number of instances where the shippingcompany has to make multiple attempts to deliver packages, and itreduces the number of times consumers have to pick up their packagesfrom the shipping company.

Abstracted Functional View of the Extensible Devices and ServicesPlatform of FIG. 2

FIG. 3 illustrates an abstracted functional view of the extensibledevices and services platform 200 of FIG. 2, with particular referenceto the processing engine 206 as well as devices, such as those of thesmart-home environment 100 of FIG. 1. Even though devices situated insmart-home environments will have an endless variety of differentindividual capabilities and limitations, they can all be thought of assharing common characteristics in that each of them is a data consumer302 (DC), a data source 304 (DS), a services consumer 306 (SC), and aservices source 308 (SS). Advantageously, in addition to providing theessential control information needed for the devices to achieve theirlocal and immediate objectives, the extensible devices and servicesplatform 200 can also be configured to harness the large amount of datathat is flowing out of these devices. In addition to enhancing oroptimizing the actual operation of the devices themselves with respectto their immediate functions, the extensible devices and servicesplatform 200 can be directed to “repurposing” that data in a variety ofautomated, extensible, flexible, and/or scalable ways to achieve avariety of useful objectives. These objectives may be predefined oradaptively identified based on, e.g., usage patterns, device efficiency,and/or user input (e.g., requesting specific functionality).

For example, FIG. 3 shows processing engine 206 as including a number ofparadigms 310. Processing engine 206 can include a managed servicesparadigm 310 a that monitors and manages primary or secondary devicefunctions. The device functions can include ensuring proper operation ofa device given user inputs, estimating that (e.g., and responding to aninstance in which) an intruder is or is attempting to be in a dwelling,detecting a failure of equipment coupled to the device (e.g., a lightbulb having burned out), implementing or otherwise responding to energydemand response events, or alerting a user of a current or predictedfuture event or characteristic. Processing engine 206 can furtherinclude an advertising/communication paradigm 310 b that estimatescharacteristics (e.g., demographic information), desires and/or productsof interest of a user based on device usage. Services, promotions,products or upgrades can then be offered or automatically provided tothe user. Processing engine 206 can further include a social paradigm310 c that uses information from a social network, provides informationto a social network (for example, based on device usage), and/orprocesses data associated with user and/or device interactions with thesocial network platform. For example, a user's status as reported totheir trusted contacts on the social network could be updated toindicate when they are home based on light detection, security systeminactivation or device usage detectors. As another example, a user maybe able to share device-usage statistics with other users. In yetanother example, a user may share HVAC settings that result in low powerbills and other users may download the HVAC settings to their smartthermostat 102 to reduce their power bills.

The processing engine 206 can include achallenges/rules/compliance/rewards paradigm 310 d that informs a userof challenges, competitions, rules, compliance regulations and/orrewards and/or that uses operation data to determine whether a challengehas been met, a rule or regulation has been complied with and/or areward has been earned. The challenges, rules or regulations can relateto efforts to conserve energy, to promote health (e.g., by reducingexposure to toxins or carcinogens), to conserve money and/or equipmentlife, etc. For example, one challenge may involve participants turningdown their thermostat by one degree for one week. Those thatsuccessfully complete the challenge are rewarded, such as by coupons,virtual currency, status, etc. Regarding compliance, an example involvesa rental-property owner making a rule that no renters are permitted toaccess certain owner's rooms. The devices in the room having occupancysensors could send updates to the owner when the room is accessed.

The processing engine 206 can integrate or otherwise utilize extrinsicinformation 316 from extrinsic sources to improve the functioning of oneor more processing paradigms. Extrinsic information 316 can be used tointerpret data received from a device, to determine a characteristic ofthe environment near the device (e.g., outside a structure that thedevice is enclosed in), to determine services or products available tothe user, to identify a social network or social-network information, todetermine contact information of entities (e.g., public-service entitiessuch as an emergency-response team, the police or a hospital) near thedevice, etc., to identify statistical or environmental conditions,trends or other information associated with a home or neighborhood, andso forth.

An extraordinary range and variety of benefits can be brought about by,and fit within the scope of, the described extensible devices andservices platform 200. Thus, in one example, each bedroom of thesmart-home environment 100 can be provided with a smart wall switch 108,a smart wall plug 110, and/or smart hazard detectors 104, all or some ofwhich include an occupancy sensor, wherein the occupancy sensor is alsocapable of inferring (e.g., by virtue of motion detection, facialrecognition, audible sound patterns, etc.) whether the occupant isasleep or awake. If a serious fire event is sensed, the remotesecurity/monitoring service or fire department is advised of how manyoccupants there are in each bedroom, and whether those occupants arestill asleep (or immobile) or whether they have properly evacuated thebedroom.

Hazard Detector Hardware

Referring now to FIG. 4, illustrates an exploded perspective view of asmart hazard detector 104 that may be used as part of a smart-homeenvironment 100 as previously described. According to embodiments, thesmart hazard detector 104 corresponds to the smart hazard detector 104described in other sections of this disclosure, such as in FIG. 1. Inone embodiment, hazard detector 104 is a smoke detector that isconfigured to detect the presence of smoke and sound an alarm to audiblywarn an occupant or occupants of the home or structure of a potentialfire or other danger. In other embodiments, hazard detector 104 may be acarbon monoxide detector, heat detector, and the like. In oneembodiment, hazard detector 104 is a multi-sensing detector thatincludes a smoke detector, carbon monoxide detector, heat detector,motion detector, and the like. Many of the present teachings areparticularly advantageous for embodiments in which the hazard detector104 is a multi-sensing detector, particularly since combining thevarious sensing modes together into a single device can pose substantialchallenges with respect to one or more of device compactness, componentpowering, and overall component governance and coordination.

For convenience in describing the embodiments herein, the device 104will be referred to hereinbelow as smart hazard detector or hazarddetector 104, although it should be realized that hazard detector 104may include various other devices and that the scope of the presentteachings is not necessarily limited to hazard detectors in which smokeis required as one of the anomalies to be detected. Thus, for example,depending on the particular context as would be apparent to a personskilled in the art upon reading the instant disclosure, one or more ofthe advantageous features and embodiments described herein may bereadily applicable to a multifunctional hazard sensor that detectscarbon monoxide and motion only, or pollen and motion only, or noisepollution and pollen only, and so forth. Nevertheless, the combining ofsmoke detection functionality with other sensing functions does bringabout one or more particularly problematic issues that are addressed byone or more of the present teachings.

In one embodiment, hazard detector 104 is a roughly square orrectangular shaped object having a width of approximately 120 to 134 mmand a thickness of approximately 38 mm. Stated differently, hazarddetector 104 is a multi-sensing unit having a fairly compact shape andsize that may be easily attached to a wall or ceiling of a home orstructure so as to be able, among other functionalities, to detect thepresence of smoke and alert an occupant therein of the potential firedanger. As shown in FIG. 4, hazard detector 104 includes a mountingplate 410 that may be attached to a wall of the building or structure tosecure the hazard detector 104 thereto. Hazard detector 104 alsoincludes a back plate 420 that may be mounted to the mounting plate 410and a front casing 460 that may be coupled with or otherwise secured toback plate 420 to define a housing having an interior region withinwhich components of the hazard detector 104 are contained. A circuitboard 900 may be coupled with or attached to back plate 420. Variouscomponents may be mounted on circuit board 900. For example, a smokechamber 430 may be coupled with or mounted on circuit board 900 andconfigured to detect the presence of smoke. In one embodiment, smokechamber 430 may be mid-mounted relative to circuit board 900 so that airmay flow into smoke chamber 430 from a position above circuit board 900and below circuit board 900.

A speaker 950 and alarm device (not numbered) may also be mounted oncircuit board 900 to audibly warn an occupant of a potential fire dangerwhen the presence of smoke is detected via smoke chamber 430. Speaker950 includes a speaker body and one or more mounting flanges that allowthe speaker 950 to be coupled with or mounted on front casing 460.Speaker 950 also includes a plug or other mounting component that allowsthe speaker 950 to be electrically coupled with circuit board 900. Aspreviously described, speaker 950 may be used to audibly alert anoccupant of a room within which hazard detector 104 is positioned, or toprovide other messages to the occupant of the room. For example, speaker950 may be used to alert a firefighter or other rescuer regarding theoccupants remaining in the home or structure after a fire or otherdanger is detected or may be used to inform an occupant of a route outof the home or structure. Other components, such as a motion sensor(e.g., ultrasonic, passive IR, etc.), carbon monoxide sensor,temperature sensor, heat sensor, ambient light sensor, noise sensor,microprocessor, and the like may likewise be mounted on circuit board900 as described herein.

In one embodiment, a protective plate 440 may be attached to orotherwise coupled with circuit board 900 to provide a visually pleasingappearance to the inner components of hazard detector 104 and/or tofunnel or direct airflow to smoke chamber 430. For example, when a userviews the internal components of hazard detector 104, such as throughvents in back plate 420, protective plate 440 may provide the appearanceof a relatively smooth surface and otherwise hide the components orcircuitry of circuit board 900. Protective plate 440 may likewisefunction to direct a flow of air from the vents of back plate 420 towardsmoke chamber 430 so as to facilitate air flow into and out of smokechamber 430.

Hazard detector 104 may also include a battery pack 450 that isconfigured to provide power to the various components of hazard detector104 when hazard detector 104 is not coupled with an external powersource, such as a 120 V power source of the home or structure. In someembodiments, a cover plate 470 may be coupled with the front casing 460to provide a visually pleasing appearance to hazard detector 104 and/orfor other functional purposes. In a specific embodiment, cover plate 470may include a plurality of holes or openings that allow one or moresensors coupled with circuit board 900 to view or see through a surfaceof cover plate 470 so as to sense objects external to hazard detector104. The plurality of openings of cover plate 470 may be arranged toprovide a visually pleasing appearance when viewed by occupants of thehome or structure. In one embodiment, the plurality of openings of coverplate 470 may be arranged according to a repeating pattern, such as aFibonacci or other sequence.

Transparent Lens Button, PIR, Light Ring, Etc.

A lens button 1200 may be coupled with or otherwise mounted to coverplate 470. Lens button 1200 may be attached to the hazard detector 104so as to be centrally positioned with respect to cover plate 470. Lensbutton 1200 includes a front surface that faces a room in which thehazard detector 104 is positioned and a rear surface that is oppositethe front surface. Lens button 1200 provides a visually appealingsurface that may be pressed by a user to provide input to hazarddetector 104 and/or for various other purposes, such as quieting analarm device. Lens button 1200 may also be transparent to one or moresensors positioned behind lens button 1200, to allow the one or moresensors to view through the lens button 1200 for various purposes. Forexample, in one embodiment a passive IR sensor (not shown) is positionedbehind the lens button 1200 and configured to view external objectsthrough lens button 1200 to detect the presence of an occupant oroccupants within the home or structure. In some embodiments, lens button1200 may also function as a button that is pressable by a user to inputvarious commands to hazard detector 104, such as to shut off an alarmthat is triggered in response to a false or otherwise harmlesscondition.

The rear surface of lens button 1200 may have a Fresnel lensingcomponent or element integrally formed thereon that allows one or morePIR sensors, or another sensor (e.g., CCD camera), positioned behindlens button 1200 to view far into the room in which hazard detector 104is positioned. Lens button 1200 is typically positioned axially in frontof the PIR or other sensor(s) to direct infrared radiation onto thesensor device. The PIR sensor(s) may be communicatively coupled withcircuit board 900 to provide information thereto and/or receiveinformation therefrom. Further, the Fresnel lens element is formed onthe rear surface of lens button 1200 so as to be hidden from externalview. Lens button 1200 provides a visually pleasing contour that maymatch a contour of an exterior of cover plate so that when coupled withcover plate, lens button 1200 and cover plate have a visually continuouscontour. Similarly, the Fresnel lens element may be contour-matched to acontour of the rear surface of lens button 1200. The Fresnel lenselement may be made from a high-density polyethylene (HDPE) that has aninfrared transmission range appropriate for sensitivity to human bodies.

In one embodiment, the Fresnel lens element may include a plurality ofconcentrically arranged rings that each include a plurality of lensletsand that each provide a slightly different viewing cone. Eachconcentrically arranged ring may provide a progressively larger viewingarea or cone than a concentrically arranged located radially closer to acentral axis of lens button 1200. In one embodiment, an internal angleof the viewing cones provided by the Fresnel lens element may vary frombetween about 15° and about 150° so as to provide a viewing radius on afloor or wall positioned directly in front of the hazard detector 104 ata distance of approximately 10 feet of between about 0.5 m and about 8.8m. In this manner, the PIR sensor, or other sensor, positioned behindlens button 1200 may easily detect the presence of an occupant within aroom in which hazard detector 104 is positioned.

Positioned distally behind lens button 1200 may be a light ring 1220that is configured to receive light, such as from an LED or anotherlight emitting element, and disperse the light within ring 1220 toprovide a desired visual appearance, such as a halo appearance aroundand behind lens button 1200. Positioned distally behind light ring 1220may be a flexible circuit board 1240 that includes one or moreelectrical components, such as a PIR sensor, LEDs, and the like.Flexible circuit board 1240 (hereinafter flex ring 1240) may beelectrically coupled with circuit board 900 to communicate and/orreceive instructions from one or more microprocessors mounted on acircuit board (not shown) during operation of hazard detector 104. Theassembled hazard detector 104 provides a compact yet multifunctionaldevice.

Light Ring Indicates if Everything is Okay or if Attention is Needed

In still another embodiment, the light ring 1220 can provide anindication regarding whether everything is okay or whether somethingrequires the user's attention. For example, the ambient light sensor isused to determine when an occupant turns off the lights in a room, andlight ring 1220 glows a particular color or in a particular pattern toindicate that everything is okay or that something needs the occupant'sattention. For example, if everything is okay, the light ring 1220 glowsgreen for two seconds. However, if something needs to be addressed, thelight ring 1220 glows yellow, for example. This could indicate thathazard detector 104 is improperly placed, the battery is low, there is aproperly with the WiFi connection, etc. This yellow glow is not analarm, but instead is just a warning that something needs to beaddressed.

In some embodiments, the PIR sensor may be replaced with an optical CCDsensor. In such embodiments, the Fresnel lens may be a true opticalimaging lens for light in the visible spectrum. The CCD sensor mayprovide optical pictures and/or video of individuals and/or objectswithin the room and within a field of view of the CCD sensor. The lensmay also serve as a user-pressable button. In other embodiments, the PIRsensor, Fresnel lens, and/or CCD sensor may be incorporated in any of avariety of different smart-home devices, such as security cameras,doorbells, garage door openers, entertainment devices, and so forth.Essentially, these components may be incorporated into any device wherean occupancy detecting function of a PIR sensor and/or CCD sensor mightbe useful and where there is a need for a front selectable button.Further, according to embodiments, an ultrasonic occupancy sensor can beused instead of or in addition to the PIR sensor. Still further,according to embodiments, near-field range detection (e.g., BLUETOOTH,NFC, etc.) and/or audio detection using noise sensors can also be usedfor occupancy detection.

In embodiments, the color of the light ring 1220 of the hazard detector104 may be adjusted for user enjoyment and/or information based onvariables such as time of year and/or hazard status. For example, theproduced halo light may glow orange around the Thanksgiving holiday andmay glow white each time snow fall occurs in the area. In anotherembodiment, the color of the light ring 1220 may be adjusted to indicatepotential issues within the home, such as a malfunctioning appliance orother component. For example, a smart thermostat may detect anabnormality with the heating system of the home and relay thisinformation to the hazard detector 104. The hazard detector 104 mayflash red to indicate to the occupant that a potential issue has beendetected and/or to warn the occupant to investigate the potential issue.An email or message may be sent to the occupant by one of the smart-homedevices (e.g., smart hazard detector 104, smart thermostat, and thelike) to notify the occupant of the detected issue. In some embodiments,the light ring 1220 may flash a number of times, or change color, toindicate the room in which the potential abnormality was detected. Forexample, the hazard detector 104 could flash once for a first room(e.g., kitchen), twice for a second room (e.g., master bedroom), and thelike.

In some embodiments, components in addition to or instead of the PIRsensor may be positioned behind the lens button 1200. For example, inone embodiment a microphone (not shown) may be positioned behind thelens button 1200 or elsewhere on the hazard detector 104. The microphonecan be operated to listen to noises that occur within the room in whichthe hazard detector 104 is positioned. In a specific embodiment, themicrophone can be activated and the noise transmitted to another roomfor various purposes, such as monitoring the activity level of a newbornchild or determining if an intruder has entered the home.

Referring now to FIGS. 5A and 5B, illustrated are front and rearperspective views of circuit board 900. Circuit board 900 includes amain body 902 having a front side or surface and a rear side or surface.As described herein, various electrical components are mounted oncircuit board 900. In some embodiments, these components may be mountedon the front surface of circuit board 900, on the rear surface ofcircuit board 900 opposite the front surface, or on both surfaces of thecircuit board 900. For example, in a specific embodiment one or moremicroprocessors and/or other processor related components may be mountedon the rear surface of circuit board 900 facing protective plate 440while one or more functional components (e.g. an alarm device, COdetector, speaker, motion sensors, Wi-Fi device, Zigbee device, and thelike) are mounted on a front surface of circuit board 900 facing a roomof the home or structure in which the hazard detector 104 is positioned.Other components may be mid-mounted relative to circuit board 900 sothat opposing surfaces are positioned on opposing sides of the circuitboard 900 as described herein.

As shown in FIG. 5A, in a specific embodiment the front surface ofcircuit board 900 may include a CO detector 970 that is configured todetect the presence of carbon monoxide gas and trigger an alarm device960 if the carbon monoxide gas levels are determined to be too high. Thealarm device 960 (which can be a piezoelectric buzzer having anintentionally shrill or jarring sound) may likewise be mounted on thefront surface of circuit board 900 so as to face an occupant of the roomin which the hazard detector 104 is positioned to alarm the occupant ofa potential danger. Alarm device 960 may be configured to produce one ormore sounds or signals to alert the occupant of the potential danger.The front surface may further include an area 952 in which a speaker 950is positioned. Speaker 950 may be configured to provide audible warningsor messages to the occupant of the room. For example, speaker 950 mayalert the occupant of a potential danger and instruct the occupant toexit the room. In some embodiments, speaker 950 may provide specificinstructions to the occupant, such as an exit route to use when exitingthe room and/or home or structure. Other messages may likewise becommunicated to the occupant, such as to alert the occupant that thebatteries are low, that CO levels are relatively high in the room, thathazard detector 104 needs periodic cleaning, or alert the occupant ofany other abnormalities or issues related to hazard detector 104 orcomponents thereof.

Circuit board 900 may also include one or more motion sensors mounted onthe front surface thereof. The motion sensors may be used to determinethe presence of an individual within a room or surrounding area ofhazard detector 104. This information may be used to change thefunctionality of hazard detector 104 and/or one or more other devicesconnected in a common network as described previously. For example, thisinformation may be relayed to a smart thermostat to inform thethermostat that occupants of the home or structure are present so thatthe smart thermostat may condition the home or structure according toone or more learned or programmed settings. Hazard detector 104 maylikewise use this information for one or more purposes, such as to quietthe alarm device (e.g. gesture hush) as described herein or for variousother reasons.

In one embodiment, a first ultrasonic sensor 972 and a second ultrasonicsensor 974 may be mounted on the front surface of circuit board 900. Thetwo ultrasonic sensors, 972 and 974, may be offset axially so as topoint in slightly different directions. In this orientation, eachultrasonic sensor may be used to detect the motion of an individualbased on an orientation of the hazard detector 104 relative to the roomand/or occupant. Detecting the motion of the individual may be used toquiet the alarm device as described herein (i.e., gesture hush) or forany other reason. In one embodiment, an axis of the first ultrasonicsensor 972 may be oriented substantially outward relative to hazarddetector 104 while an axis of the second ultrasonic sensor 974 isoriented at an angle relative to the axis of first ultrasonic sensor972. The first ultrasonic sensor 972 may sense motion of an individualwhen the hazard detector 104 is mounted on a ceiling of the home orstructure. Because the first ultrasonic sensor 972 is orientedsubstantially outward relative to hazard detector 104, the firstultrasonic sensor 972 essentially looks straight down on individualsbeneath hazard detector 104. The second ultrasonic sensor 974 maysimilarly sense motion of the individual when the hazard detector 104 ismounted on a wall of the home or structure. Because the secondultrasonic sensor 974 is oriented at an angle relative to the firstultrasonic sensor 972 and hazard detector 104, the second ultrasonicsensor essentially looks downward toward the floor when the hazarddetector 104 is mounted on a wall of the home or structure, rather thanlooking directly outward as first ultrasonic sensor 972. In oneembodiment, the angular offset of the two ultrasonic sensors may beapproximately 30° or any other desired value.

In another embodiment, the two ultrasonic sensors, 972 and 974, may bereplaced by a single ultrasonic sensor that is configured to rotatewithin hazard detector 104 so that the single ultrasonic sensor iscapable of looking straight outward similar to first ultrasonic sensor972 or capable of looking downward similar to second ultrasonic sensor974. The single ultrasonic sensor may be coupled to circuit board 900via a hinge that allows the ultrasonic sensor to rotate based on theorientation of hazard detector 104. For example, when hazard detector104 is mounted to a ceiling of the home or structure, gravity may orientthe ultrasonic sensor so as to look straight downward; whereas whenhazard detector 104 is coupled to a wall of the home or structure,gravity may cause the ultrasonic sensor to rotate via the hinge and lookdownward toward a floor and relative to hazard detector 104. In anotherembodiment, a motor may be coupled with the single ultrasonic sensor soas to rotate the ultrasonic sensor based on the orientation of hazarddetector 104. In this manner, the ultrasonic sensor may always point ina direction that is likely to detect motion of an individual within theroom or space surrounding the hazard detector 104. In yet anotherembodiment, the single ultrasonic sensor may have a wide field of viewthat is able to substantially accommodate both mounting positions of thetwo ultrasonic sensors 972 and 974.

As shown in FIGS. 5A and 5B, body 902 of circuit board 900 also includesa substantially centrally located aperture 904 through which smokechamber 430 is inserted so as to mid-mount the smoke chamber 430relative to circuit board 900. Aperture 904 may also include a pair ofnotches 906 through which wires are inserted to electrically couple thesmoke chamber 430 with circuit board 900. As previously described,mid-mounting of the smoke chamber 430 through an aperture 904 allowssmoke and air to enter smoke chamber 430 from both the front surface orside of circuit board 900 and the rear surface or side of circuit board900. Various aspects of the electrical components on the circuit board900 are now described, the positions thereon of many of which will beapparent to the skilled reader in view of the descriptions herein andFIGS. 5A-5B. Included on the circuit board 900 can be severalcomponents, including a system processor, relatively high-power wirelesscommunications circuitry and antenna, relatively low-power wirelesscommunications circuitry and antenna, non-volatile memory, audio speaker950, one or more interface sensors, a safety processor, safety sensors,alarm device 960, a power source, and powering circuitry. The componentsare operative to provide safety detection features and user interfacefeatures using circuit topology and power budgeting methods thatminimize power consumption. According to one preferred embodiment, abifurcated or hybrid processor circuit topology is used for handling thevarious features of the hazard detector 104, wherein the safetyprocessor is a relatively small, relatively lean processor that isdedicated to core safety sensor governance and core alarmingfunctionality as would be provided on a conventional smoke/CO alarm, andwherein the system processor is a relatively larger, relativelyhigher-powered processor that is dedicated to more advanced featuressuch as cloud communications, user interface features, occupancy andother advanced environmental tracking features, and more generally anyother task that would not be considered a “core” or “conventional”safety sensing and alarming task.

By way of example and not by way of limitation, the safety processor maybe a Freescale KL15 microcontroller, while the system processor may be aFreescale K60 microcontroller. Advantageously, the safety processor isprogrammed and configured such that it is capable of operating andperforming its core safety-related duties regardless of the status orstate of the system processor. Thus, for example, even if the systemprocessor is not available or is otherwise incapable of performing anyfunctions, the safety processor will attempt to perform its core taskssuch that the hazard detector 104 still meets all industry and/orgovernment safety standards that are required for smoke, CO, and/orother safety-related monitoring for which the hazard detector 104 isoffered (provided, of course, that there is sufficient electrical poweravailable for the safety processor to operate). The system processor, onthe other hand, performs what might be called “optional” or “advanced”functions that are overlaid onto the functionality of the safetyprocessor, where “optional” or “advanced” refers to tasks that are notspecifically required for compliance with industry and/or governmentalsafety standards. Thus, although the system processor is designed tointeroperate with the safety processor to improve the overallperformance, feature set, and/or functionality of the hazard detector104, its operation may not be required in order for the hazard detector104 to meet industry and/or government safety standards. Being generallya larger and more capable processor than the safety processor, thesystem processor may consume more power than the safety processor whenboth are active.

Similarly, when both processors are inactive, the system processor maystill consume more power than the safety processor. The system processorcan be operative to process user interface features and monitorinterface sensors (such as occupancy sensors, audio sensors, cameras,etc., which are not directly related to core safety sensing). Forexample, the system processor can direct wireless data traffic on bothhigh and low power wireless communications circuitry, accessnon-volatile memory, communicate with the safety processor, and causeaudio to be emitted from speaker 950. As another example, the systemprocessor can monitor interface sensors to determine whether any actionsneed to be taken (e.g., shut off a blaring alarm in response to a userdetected action to hush the alarm). The safety processor may beoperative to handle core safety related tasks of the hazard detector104. The safety processor may poll safety sensors (e.g., smoke, CO) andactivate alarm device 960 when one or more of its safety sensorsindicate a hazard event is detected, or if another hazard detector 104broadcasts information of an alarm status requiring an audible alarm(see FIG. 18B). The safety processor may operate independently of thesystem processor and may activate alarm device 960 regardless of whatstate the system processor is in. For example, if the system processoris performing an active function (e.g., performing a Wi-Fi update) or isshut down due to power constraints, the safety processor may stillactivate alarm device 960 when a hazard event is detected.

In some embodiments, the software running on the safety processor may bepermanently fixed and may not be updated via a software or firmwareupdate after the hazard detector 104 leaves the factory. Compared to thesystem processor, the safety processor is a less power consumingprocessor. Using the safety processor to monitor the safety sensors, asopposed to using the system processor to do this, can yield powersavings because safety processor may be constantly monitoring the safetysensors. If the system processor were to constantly monitor the safetysensors, power savings may not be realized. In addition to the powersavings realized by using safety processor for monitoring the safetysensors, bifurcating the processors can also ensure that the safetyfeatures of the hazard detector 104 always work, regardless of whetherthe higher level user interface works. The relatively high powerwireless communications circuitry can be, for example, a Wi-Fi modulecapable of communicating according to any of the 802.11 protocols.

By way of example, the relatively high power wireless communicationscircuitry may be implemented using a Broadcom BCM43362 Wi-Fi module. Therelatively low power wireless communications circuitry can be a lowpower Wireless Personal Area Network (6LoWPAN) module or a ZigBee modulecapable of communicating according to a 802.15.4 protocol. For example,in one embodiment, the relatively low power wireless communicationscircuitry may be implemented using an Ember EM357 6LoWPAN module. Thenon-volatile memory can be any suitable permanent memory storage suchas, for example, NAND Flash, a hard disk drive, NOR, ROM, or phasechange memory. In one embodiment, the non-volatile memory can storeaudio clips that can be played back using the speaker 950. The audioclips can include installation instructions or warnings in one or morelanguages. The interface sensors can includes sensors that are monitoredby the system processor, while the safety sensors can include sensorsthat are monitored by the safety processor.

The interface sensors can include, for example, an ambient light sensor(ALS) (such as can be implemented using a discrete photodiode), a noisesensor, a passive infrared (PIR) motion sensor (such as can beimplemented using an Excelitas PYQ1348 module), and one or moreultrasonic sensors (such as can be implemented using one or moreManorshi MS-P1640H12TR modules). The safety sensors can include, forexample, the smoke detection chamber 430 (which can employ, for example,an Excelitas IR module), the CO detection module 970 (which can employ,for example, a Figaro TGS5342 sensor), and a temperature and humiditysensor (which can employ, for example, a Sensirion SHT20 module). Thepower source can supply power to enable operation of the hazard detectorand can include any suitable source of energy. Embodiments discussedherein can include AC line power, battery power, a combination of ACline power with a battery backup, and externally supplied DC power(e.g., USB supplied power). Embodiments that use AC line power, AC linepower with battery backup, or externally supplied DC power may besubject to different power conservation constraints than battery onlyembodiments.

Advantageously, battery-only powered embodiments are designed to managepower consumption of a finite energy supply such that hazard detector104 operates for a minimum period of time of at least seven (7), eight(8), nine (9), or ten (10) years. Line powered embodiments are not asconstrained. Line powered with battery backup embodiments may employpower conservation methods to prolong the life of the backup battery. Inbattery-only embodiments, the power source can include one or morebatteries, such as the battery pack 450. The batteries can beconstructed from different compositions (e.g., alkaline or lithium irondisulfide) and different end-user configurations (e.g., permanent, userreplaceable, or non-user replaceable) can be used. In one embodiment,six cells of Li—FeS₂ can be arranged in two stacks of three. Such anarrangement can yield about 27000 mWh of total available power for thehazard detector 104.

Speaker of Hazard Detector as Doorbell

According to embodiments, hazard detector 104 functions as a doorbellcharm. For example, hazard detector 104 may communicate via the meshnetwork with the smart doorbell 106, and receive messages from the smartdoorbell 106 regarding when to output a doorbell sound via speaker 950.For example, upon a visitor approaching an exterior door of thesmart-home environment 100 and touching, pressing, or otherwiseactivating the smart doorbell 106, the smart doorbell 106 sends acorresponding message to the hazard detector 104. Upon receiving themessage from the smart doorbell 106, the hazard detector 104 determinesan appropriate response, which may include outputting the doorbellsound. For example, upon receiving the message the hazard detector 104may first use its occupancy sensing capabilities to determine if theroom or area in which it is located is occupied and, possibly, it mayalso determine which occupants are in the room using facial recognitiontechniques as well as other techniques used to identify an individual's“signature”.

In some cases, if the room or area is unoccupied, the hazard detector104 will not output the doorbell sound and it will instead remainsilent. In still other cases, hazard detector 104 will not output thedoorbell sound if it determines that an occupant is a child, pet, or anadult or child sleeping in the room or area. For example, to determineif an occupant is sleeping in the room, hazard detector 104 may notewhen an occupant enters the room or area and infer that the occupant issleeping if the occupant does not leave the room and if there is nomovement in the room for a period. As discussed below with reference toFIGS. 13 & 14, according to embodiments, a user can program hazarddetector 104 so that it knows its location within the home. For example,hazard detector 104 can know if it is in a kitchen, a bedroom, a livingroom, etc. In these embodiments, the feature of not outputting thedoorbell sound if hazard detector 104 determines that an occupant is inthe room sleeping will only be active if the hazard detector knows thatit is located in a bedroom. Thus, if hazard detector 104 is located inthe living room or the kitchen, it will not first assess if an occupantis asleep in the room before outputting the doorbell sound.

In other embodiments, if hazard detector 104 knows that it is located ina bedroom, it will not output the doorbell sound if the room isoccupied. According to these embodiments, hazard detector 104 will notattempt to determine whether the occupant is awake or asleep. Thisreduces processing burden and saves power, as well as reduces thelikelihood of making an error by incorrectly inferring that an occupantis asleep or awake. In still other embodiments, if hazard detector 104knows that it is in a kid's bedroom, as indicated by the user during setup, it will never output the doorbell sound.

As mentioned above, embodiments of the present invention, e.g., hazarddetectors 104, may be paired with an online management account. Thispairing may be accomplished during the setup process for a smart hazarddetector. Examples of this setup process according to the presentinvention are discussed in the next section.

Setting Up the Hazard Detector

FIGS. 1-5B above outline numerous features and benefits of intelligent,network-connected, multi-sensing hazard detection units or hazarddetectors of the present invention. In order to achieve some of thesebenefits, smart hazard detectors may need to be set up and/or “paired”with an online management account. Similarly, although not illustratedhere, smart thermostats 102 may also be paired with the onlinemanagement account, as part of a smart thermostat 102 installationprocess. In particular, when smart thermostat 102 is installed, aninstaller of smart thermostat 102 may be queried as to a type of heatingsystem is being controlled. In embodiments, smart thermostat stores theanswer in memory therein. This is relevant to embodiments herein thatcontrol fossil fuel-based heating systems, which may generate CO as acombustion byproduct.

FIG. 6 illustrates a method 1300 for setting up a hazard detector andestablishing a pairing between the hazard detector and an onlinemanagement account, according to an embodiment. Certain steps of method1300 are discussed in detail below, and some steps are discussed withreference to additional figures that may provide physical illustrationsrelated to the steps of method 1300. It should be appreciated thatmethod 1300 is an exemplary method of setting up and pairing a hazarddetector and that some illustrated steps may not be necessary orapplicable, and other, additional steps may be appropriate.

Sending Unique Code for Hazard Detector to Server

At step 1305 of method 1300, a central server or a cloud-computingsystem, e.g., server 164, may receive input corresponding to a code.This code may be the unique ID of a hazard detector. The code may alsobe associated with additional information stored on a server, e.g., thehazard detector's manufacture date, the software version that wasinitially installed on the hazard detector and/or other informationabout the hazard detector. Before the server can receive this code instep 1305, a user first may need to obtain the code from a hazarddetector, e.g., hazard detector 104. The code may be contained in theproduct packaging of the hazard detector or displayed on the hazarddetector and provided to server 164 via an app or a webpage configuredto provide communication to server 164.

Receiving User's Account Credentials

At step 1310 of method 1300, a central server or a cloud-computingsystem, e.g., server 164, may receive input corresponding to credentialsfor accessing an online management account.

Link Hazard Detector to Online Account

At step 1315, a central server or a cloud-computing system, e.g., server164, may associate hazard detector 104 and an online management accountusing a code and credentials for the online management account. This mayalso allow data, e.g., home data 202, to be collected, stored and linkedto and/or accessible at a user's online management account.Additionally, this association may allow for remote access and/or remoteor distributed control of hazard detector 104 via a user's onlinemanagement account. However, in order for data collected from and/orremote control of hazard detector 104 to be possible, hazard detector104 may need to have a network connection.

Tell Hazard Detector where in the Home it is Located

At step 1320 of method 1300, hazard detector 104 receives user inputcorresponding to its location within a home or building (e.g., userinputs information that tells hazard detector where it is located). Insome embodiments, hazard detector 104 transmits the location informationto a central server or a cloud-computing system. The user input could belocation information, such as indication of a room type or room namewhere hazard detector 104 is being installed. The location informationcould be stored locally on hazard detector and/or at the user's onlinemanagement account and used to enhance the features of services 204provided by and to hazard detector 104.

The location information may be used to further configure hazarddetector 104. For example, the location of hazard detector 104 may beused to alter the way alerts are provided to users and/or how hazarddetector 104 interprets characteristics measured by its sensors. Morespecifically, for example, hazard detector 104 may account for theenvironmental characteristics of a kitchen by adjusting alarm thresholdto make the hazard detector less sensitive to smoke and heat commonlyobserved in kitchens. Also for example, hazard detector 104 may accountfor increased amounts of humidity since higher levels of humidity is acharacteristic of kitchens (e.g., higher humidity in kitchen whensomething is boiling on the stovetop). Further for example, hazarddetector 104 may alter the alert or alarm sequence, such as by providinga user more opportunities to preemptively “hush” an alarm for a known,low level smoke condition. In another example, hazard detector 104 maybe located in a bedroom. To account for the environmentalcharacteristics of a bedroom, hazard detector 104 may become moresensitive to smoke and CO and/or it may increase its alarm volumes forthe purpose of waking up sleeping individuals upon detection of apotentially dangerous condition.

Hazard Detector Advises which Features are Appropriate for itsParticular Location

At step 1325 of method 1300, a user is advised of recommended settingsfor hazard detector 104 based on the location of the hazard detector.Some features of hazard detector 104 may not be desirable for somelocations and, when installed in those locations, hazard detector 104can be placed in a limited operation mode in which one or more of thosefeatures are disabled. For example, it has been found that garages areinadvisable locations in which to place a CO detector. However, it hasalso been found that garages are advisable locations in which to placeheat detectors. Accordingly, as illustrated in FIG. 7, if the userinputs “Garage” as the location at step 1320, then according to step1325, application 1414 provides user with a message 1443, informing theuser that CO detection is not advisable in garages and giving the userthe option of turning off the CO detection function. FIG. 8 illustratesanother example of application 1414 providing recommended setting basedon the location of the hazard detector. Here, application 1414 providesa list 1447 of recommended settings for the location of the hazarddetector 104. As illustrated, application 1414 recommends turning on thesmoke detection, heat detection, and nightlight functions, but disablingthe CO detection for this hazard detector that is located in a Garage.The user can accept these recommended setting by pressing button 1444,or the user can change the recommended settings by pressing button 1449next to each of the listed settings to toggle between “off” and “on”,and then press button 1449 when the settings are to the user's liking.

Another example is illustrated in FIG. 9. In this example, the hazarddetector 104 is being installed in a Kid's Bedroom. According to theillustrated recommended feature list 1447 for a kid's bedroom, thedefault setting for the nightlight function is “off”, and “on” is thedefault setting for smoke detection, CO detection, and heat detection.The nightlight is set to “off” so that the light will not disturb peoplewhile they are sleeping. However, for other rooms, such as living roomsand kitchens, it should be appreciated that the default setting for thenightlight function is “on”.

At step 1330 of method 1300, responsive to being advised of recommendedsettings for hazard detector 104 based on the location of the hazarddetector, the user inputs their selections of which features to turn onand off. As illustrated in FIG. 7, responsive to being advised that COdetection is not recommended in Garages, the user can press button 1445to answer yes or no to the question of whether to turn off the COdetection function. After selecting user or no the user can press button1444 to submit the selection. In FIG. 8, responsive to being presentedwith a list 1447 of recommended functions for a location, user can pressbuttons 1449 to select which features the user wants turned off or on.The user can then press button 1444 to input the selections.

Hazard Detector Auto-Tests to ‘See’ if it is in a Bad Location

At step 1335 of method 1300, a test is performed to make sure hazarddetector 104 is not installed in a bad location, such as where itssensor are obstructed. According to an embodiment, hazard detector 104executes a self-test where it uses its ultrasonic sensor(s) to determineits position relative to walls, ceilings, floors, and/or other objectslocated in the room. For example, hazard detector uses its ultrasoundsensor to ‘see’ if it is located too deep in a corner or behind anobstruction, where it does not have unobstructed access to monitor theconditions of the room, including detecting occupancy of the room. Inone embodiment, hazard detector 104 tests to determine whether it is toofar in a corner by using its ultrasound sensor to detect whether theperpendicular walls are within a predetermined distance.

FIG. 10 illustrates an example of the physical process associated withstep 1335. An interface may be provided at application 1414 on mobilecomputing device 1416 to explain that the hazard detect is ready to testwhether it is installed in a good location, where it can optimallydetect hazardous conditions. In the illustrated example, the user canpress button 1446 to begin the test. Also, as illustrated in FIG. 10,hazard detector 104 can output an audible message saying, “Press buttonto test my location”. In response, users can press button 1200 indirection 1410 to begin the test. If the test fails due to hazarddetector 104 being position too close to an object, such as a wall,application 1414 will display message, or hazard detector 104 willoutput a voice message, indicating that hazard detector 104 appears tobe too close to an object, such as a wall, and recommending relocationof hazard detector 104 to another position.

At step 1340 of method 1300, a central server or a cloud-computingsystem may confirm setup and pairing of hazard detector 104. Forexample, at step 1340, the application 1414 provides a confirmationmessage that confirms the pairing association created at step 1310 andthe setup selections made at steps 1320 and 1330. FIG. 14R illustratesan example of the physical process associated with step 1340.Application 1414 may display the screen shown in FIG. 11 in order toprovide confirmation that the setup for hazard detector 104 is complete.Hazard detector 104 may also generate a corresponding audio and/orvisual indicator. For example, as shown in FIG. 11, the hazard detectormay generate the following speech when “Kids Bedroom” is the locationselected at step 1320: “Kids Bedroom Device ready”. Alternatively,hazard detector 104 may generate other audio and/or visual confirmationof the successful association. These confirmations signify that hazarddetector 104 has been associated with the selected location at theonline management account on sever 164. The user may tap a continuebutton 1446 to confirm that the confirmation screen has been viewed.Although additional steps may not be required in order to complete thesetup of hazard detector 104, the user may still proceed with additionalsteps to verify hazard detector 104 is functioning properly. An exampleof this verification process is illustrated in the following figures.

In some embodiments, the input provided at application 1414 duringmethod 1300 may be accomplished using speech recognition, air gestures,eye tracking and blink detection and/or other input means. Again, asmentioned above, the method 1300 may also occur at a webpage ofcomputing device. Furthermore, although the communication between hazarddetector 104 and a portable computing device 1416 is described above asoccurring over Wi-Fi, other wireless protocols supported by both hazarddetector 104 and portable computing device 1416 may be used in thealternative. Also, while a limited number of visual and audio indicatorsgenerated by hazard detector 104 were described above, other indicatorsmay also be generated by hazard detector 104 during method 1300.

Setting Up and Pairing Multiple Hazard Detectors in a Single Home

In some situations, a user may wish to add more than one hazard detectorto a smart-home environment. In some embodiments, method 1300 may berepeated for each additional hazard detector in order to pair it withthe online management account. Alternatively, the method for addingadditional hazard detectors may vary from method 1300 in a manner thatreduces or minimizes an amount of user effort involved. An example of amethod that uses method 1300 to add a first hazard detector, and amodified version of method 1300 to add an additional hazard detector, isshown in FIG. 12.

FIG. 12 illustrates a method for pairing two or more hazard detectorsand an online management account, according to an embodiment. At step1505 of method 1500, an embodiment of method 1300 may be performed inorder to pair a first hazard detector and an online management account.

At step 1510, instructions are transmitted that cause the first hazarddetector to establish wireless communication between the first hazarddetector and a second hazard detector. To accomplish step 1510, user mayopen or install and open an app, e.g., application 1414, on a computingdevice, e.g., computing device 1416. Alternatively, a webpage configuredto communicate with the online management account may be used inperforming step 1510. Upon opening the app, an option to add anotherhazard detector, a second hazard detector, may be selected at the appinterface. Using a wireless protocol such as Wi-Fi the app may thentransmit instructions via a server, e.g., server 164, and internet 162to the first hazard detector. For example, the first hazard detector maybe instructed to broadcast across a 6LoWPAN network, or another wirelessprotocol that requires very little power, such as Zigbee.

The 6LoWPAN wireless network broadcasted by the first hazard may use aunique network name that may be recognized by other hazard detectorsand/or assign itself one or more IPv6 addresses that include arendezvous prefix. The rendezvous prefix may help hazard detectors toidentify the networks it should join. Alternatively, the 6LoWPAN networkmay be broadcasted in another manner that allows a second hazarddetector to recognize it as a network that should be joined. The secondhazard detector may also broadcast a 6LoWPAN network in a similarmanner. When one hazard detector discovers another hazard detector's6LoWPAN network, it may terminate its joining network and connect to thenetwork broadcasted by the other hazard detector. Thus, the first hazarddetector may join the second hazard detector's network and vice versa.Either way, a wireless communication may be established in this mannerbetween the first hazard detector and the second hazard detector overthe 6LoWPAN or another low power wireless protocol.

At step 1515, instructions are transmitted that cause the first hazarddetector to share network credentials with the second hazard detector.The instructions may originate from an app and may be routed to thefirst hazard detector via server 164. Thereafter, the first hazarddetector may leverage the wireless communication established between itand the second hazard detector over the second wireless protocol inorder to share network credentials. The network credentials may includea network router name and password for connecting to internet 162. Thisnetwork router may also be the network router that the first hazarddetector is using to transmit the instructions of step 1510. The secondhazard detector may use the network credentials to connect to theinternet 162. Thereafter, the first and second hazard detectors maydisable their 6LoWPAN networks and use Wi-Fi to connect to the internetvia a network router in order to communicate with the app and/or anonline management account located at server 164.

At step 1520, a modified version of method 1300 may be performed inorder to establish a new pairing between the second hazard detector andthe online management account using the first wireless protocol. Themodified version of method 1300 of step 1520 may include all the stepsof embodiments and variations of method 1300 with a few exceptions. Forexample, at the modified step of 1310, step 1520 may automatically usethe online management account credentials already stored at the app toassociate the second hazard detector with the online management accountinstead of creating or entering online management account credentials.In addition, step 1520 would clearly not require connecting the secondhazard detector to internet 162, because that connection was alreadyaccomplished at step 1515 above.

Accordingly, method 1500 may allow for adding additional hazarddetectors in a manner that requires less user effort than method 1300.Steps 1510-1525 may be repeated to add a third or additional hazarddetectors to a smart-home environment.

As mentioned above, a hazard detector according to the present inventionmay provide audio and/or visual indicators during the setup process toguide and provide feedback to the user. Similar audio and/or visualfeedback may be provided during method 1500. Again, while a limitednumber of visual and audio indicators generated by hazard detector 104were described above, other indicators may also be generated by hazarddetector 104 during method 1300 and/or 1500. Additional examples may befound in the “Smart Hazard Detector Alerts and Indicators” sectionbelow.

In various embodiments, visual effects provided by hazard detector 104could be varied in a number of different ways. For example, variousfeatures may be activated to change faster or slower, brighter ordimmer, for a specific number of animation cycles, with only some of thelight participating, and using different colors, e.g., white, blue,green, yellow and red.

These visual effects may be generated by hazard detector 104 for avariety of specified purposes. For example, a specific color, animation,animation speed, etc. or combinations thereof may represent one or moreof the following alerts or notifications provided a hazard detector:booting up, selecting language, ready for connections, connected toclient, button pressed, button pressed for test, countdown to test, testunder way, test completed, pre-alarms, smoke alarms, carbon monoxidealarms, heat alarms, multi-criteria alarms, hushed after alarm,post-alarm, problems, night light state, reset, shutdown begin,shutdown, safely light, battery very low, battery critical, powerconfirmation, and more. By way of example and not by way of limitation,FIG. 13 illustrates visual vocabulary for visual effects that may beused by hazard detector 104 and FIG. 14 illustrates an animation/colormatrix of visual effects that may be used by hazard detector 104.

As mentioned above and specifically described with respect to thephysical process representations of FIGS. 7-11, audio effects mayaccompany the visual effects or may be generated instead of visualeffects in order to provide an alert, e.g., the alerts discussed herein.

Audible Low-Battery Warning

FIG. 15 illustrates an audible low-battery warning, according toembodiments. As illustrated hazard detector 104 outputs an audiblemassage that says, “Low Battery”. The hazard detector 104 can beconfigured to provide this warning well in advance of the batteryactually dying. As illustrated, the audible warning given by the hazarddetector 104 indicates that the battery will die in approximately threemonths. It should be appreciated that hazard detector 104 can beconfigured to give the low-battery warning before or after three monthsfrom when the battery is likely to die. Further, according toembodiments, hazard detector 104 provides periodic reminders until thebattery is replaced. For example, hazard detector 104 may provide aweekly or monthly warning. In some embodiments, as illustrated in FIG.15, hazard detector 104 also provides an audible warning when the COdetector is malfunctioning. It should also be appreciated that it mayprovide an audible warning when the smoke detector or any other sensormalfunctions. As illustrated in FIG. 10 and described in correspondingsections of the specification, hazard detector 104 is configured toself-test its sensors, such as the smoke detector and the CO detector.In some examples, hazard detector uses its motion sensing capabilitiesto determine when the home is unoccupied and to conduct the self-testingat those times. As discussed above, if the self-testing reveals that oneor more sensors is malfunctioning, hazard detector 104 will audiblynotify the occupants.

Alarm Conditions

Serious Hazardous and Pre-Hazardous Conditions

According to some embodiments, alarm condition detection andnotification services are provided to detect and warn users of alarmconditions in an environment, such as a home. More particularly, hazarddetector 104 detects alarm conditions based on information obtained fromits sensors, and it provides corresponding alarms to users. According toembodiments, alarm conditions are divided into two categories:pre-hazardous conditions and serious hazard conditions. Serious hazardconditions are situations where sensor data indicates that conditions inan environment are dangerous to the health and safety of individuals inthe environment, and/or alarms are required under applicable NationalFire Protection Association (“NFPA”) or Underwriters' Laboratories(“UL”) standards. Pre-hazardous conditions are situations where thesensor data may not support a serious hazard condition, but is enough tosuggest that a pre-hazardous condition may exist in the environment(e.g., the condition may be outside the “normal” conditions recorded atthat particular location) such that it is worth notifying users so theycan investigate the condition and assess whether remedial measures arewarranted to prevent the pre-hazardous condition from escalating to aserious hazard condition.

According to embodiments, the alarm condition detection and notificationservices are applied to detect elevated levels of potentially dangeroussubstances (e.g., CO, smoke, heat, etc.) in the smart-home environment100. In some embodiments, hazard detector 104 determines whether andwhich alarm condition exists based on whether conditions in theenvironment have reached one or more thresholds.

According to some embodiments, the thresholds used to determine whetheralarm conditions exist represent trends over time in the amount ofsubstances in the environment. These types of thresholds are sometimesreferred to herein as “threshold trends”. In the following discussionand throughout the present disclosure, it is to be appreciated that anyparticular numerical levels set forth herein are for illustrativepurposes only and are not to be understood as absolute levels in anyparticular units or measurement systems. Such illustrative units,sometimes provided within quotation marks herein, are to be understoodas being hypothetical units for the sake of illustration only. ProperNFPA and UL guidelines and standards should be followed, as would bereadily apparent to a person skilled in the art. It is preferable andadvisable not to adjust actual emergency alarm thresholds, but rather toadjust thresholds for pre-hazardous conditions (sometimes called“pre-alarm” thresholds herein), as now described.

An example threshold trend is that the amount of a substance (e.g., CO,smoke, etc.) in the environment has increased by at least a 20% over atwo-week period. Thus, if the amount of the substance in the environmentincreases by only 19% over a two-week period, then no alarm condition isdetermined to exist. Similarly, if the amount of the substance in theenvironment increases by 21%, but it takes more than two weeks for thisincrease to occur, then no alarm condition is determined to exist.However, if the amount of the substance in the environment increases by21% over the two-week period, then an alarm condition is determined toexist. A particular example of a threshold trend is if smoke obscurationin the environment is above “0.5” for thirty seconds, then an alarmcondition for smoke is determined to exist. Another particular exampleof a threshold trend is if the CO-concentration level in the environmenthas exceeded “50” for two days, then an alarm condition for CO isdetermined to exist. Yet another particular example of a threshold trendis if heat has exceeded “90” for 5 minutes, then an alarm condition forheat is determined to exist.

According to other embodiments, the thresholds used to determine whetheralarm conditions exist represent amounts of one or more substances inthe environment, regardless of time. In other words, these thresholdsare based on a “snapshot” measurement of substances in the environment.These types of thresholds are sometimes referred to herein as “thresholdvalues”. A particular example of a threshold value is when CO reaches“70” instantaneously, then an alarm condition for CO is determined toexist. Another particular example of a threshold is when smokeobscuration reaches “3.0” instantaneously, then an alarm condition forsmoke is determined to exist. Yet another particular example of athreshold trend is if temperature reaches “90” instantaneously, then analarm condition for heat is determined to exist.

According to embodiments, the thresholds used by hazard detector 104 todetermine whether alarm conditions exist may be stored in memory onhazard detector 104 itself or remotely by a server, such as the centralserver and cloud-computer system 164. As described in more detail below,table 2500 of FIG. 17 provides example thresholds used by hazarddetector 104 to determine whether alarm conditions exist. According tosome embodiments, the example thresholds provided in table 2500 arethresholds for pre-hazardous conditions. In other embodiments, theexample thresholds provided in table 2500 are thresholds for serioushazard conditions.

As mentioned, hazard detector 104 may provide an alarm to users upondetermining that an alarm condition exists in an environment. In asmoke-related example, hazard detector 104 provides an alarm for smoke,indicating an alarm condition for smoke exists in the environment. Inone example, hazard detector 104 determines that an alarm conditionexists when, based on data obtained from its sensors, it observes thatconditions in the environment have reached or exceeded one or morepredetermined thresholds, including one or more of a smoke threshold, ahumidity threshold, a CO threshold, and a temperature threshold. In aparticular example, hazard detector 104 determines that an alarmcondition for smoke exists when the smoke level in the environmentexceeds a threshold trend for smoke (e.g., “0.5” obscuration for thirtyconsecutive seconds). In another smoke-related example, hazard detector104 determines that an alarm condition for smoke exists when the smokelevel in the environment exceeds a threshold trend for smoke and thehumidity level of the environment is decreasing. In other examples,hazard detector 104 determines that alarm conditions exist when the COlevel of the environment exceeds a threshold value for CO (e.g., CO>“70”instantaneously), or when the temperature of the environment exceeds athreshold trend for temperature (e.g., temperature of environmentincreases by “+10” in last three minutes).

Traditional smoke detectors are not good at distinguishing steam andsmoke. However, by using the above-mentioned thresholds for humidity,CO, and/or heat, hazard detector 104 is better able to distinguishbetween steam and smoke. For example, in the event hazard detector 104'ssmoke sensor observes increasing “smoke” levels in an environment,hazard detector 104 won't conclude that an alarm condition involvingsmoke exists, if hazard detector 104's humidity sensor detects that thehumidity in the environment is staying the same or increasing. Instead,hazard detector 104 will conclude that the “smoke” is actually steambecause humidity would decrease if fire were the source of the detected“smoke”. Similarly, in the event hazard detector 104's smoke sensorobserves increasing “smoke” levels, but its CO sensor indicates that COin the environment is staying the same or decreasing, hazard detectorwon't conclude that an alarm condition involving smoke exists. Instead,hazard detector 104 will conclude that the “smoke” is actually steambecause CO would increase if fire were the source of the detected“smoke”.

In a CO-related example, hazard detector 104 provides an alarmindicating an alarm condition for CO exists in the environment. In thisexample, hazard detector 104 determines that an alarm condition for COexists when, based on data from its sensors, it observes that conditionsin the environment have reached or exceeded one or more predeterminedthresholds used to determine whether an alarm condition for CO exists.In one example, hazard detector 104 determines that an alarm conditionfor CO exists and provides a corresponding alarm when its CO sensorobserves CO levels above a threshold trend for CO (e.g., COconcentration exceeds “50” for thirty consecutive seconds, or COconcentration exceeds “300” after a three-minute period, etc.). Itshould be appreciated that a quadratic function can be used to model thethreshold trend for CO. In an example quadratic function, time is theindependent variable and CO level is the dependent variable. If, at aparticular time, the CO level of the environment exceeds the CO levelprovided by the quadratic function for that particular time, then hazarddetector 104 determines that an alarm condition for CO exists.

In a heat-related example, hazard detector 104 provides a pre-alarmindicating a pre-hazardous condition for heat exists in the environment.In this example, hazard detector 104 determines that a pre-alarmcondition for heat exists when, based on data from its sensors, itobserves that conditions in the environment have reached or exceeded oneor more predetermined thresholds used to determine whether apre-hazardous condition for heat exists. In one example, hazard detector104 determines that pre-hazardous condition for heat exists and providesa corresponding pre-alarm when its heat sensor observes heat levelsabove a threshold value for heat (e.g., temperature exceeds “90”). Inanother example, hazard detector 104 determines that pre-hazardouscondition for heat exists and provides a corresponding pre-alarm whenits heat sensor observes temperature levels above a threshold trend forheat (e.g., temperature increased by at least “12” over the lastminute). In yet another example, hazard detector 104 determines that apre-hazardous condition for heat exists and provides a correspondingpre-alarm when its heat sensor observes temperature levels above athreshold value and above a threshold trend for heat (e.g., temperatureexceeds “90” and the temperature increased by at least “12” over thelast minute). It should be appreciated that a linear function (e.g.piecewise linear function) can be used to model the threshold trend forheat. In an example linear function, time is the independent variableand temperature is the dependent variable. If, at a particular time, thetemperature of the environment exceeds the temperature provided by thelinear function for that particular time, then hazard detector 104determines that a pre-hazardous condition for heat exists.

Under some circumstances, users may “hush” hazard detector 104 to causeit to stop “pre-alarming” and to continue monitoring the environment(see FIGS. 23, 24 and the corresponding discussion below). While hazarddetector 104 is hushed, users can investigate whether the indicatedpre-hazardous condition indeed exists and take any necessary remedialmeasures. However, if the pre-hazardous condition persists, hazarddetector 104 may provide one or more further pre-alarm(s) indicatingthat the pre-hazardous condition still exists. Further, hazard detector104 can provide a “regular” or serious hazard alarm indicating a serioushazard condition exists if the pre-hazardous condition escalates to aserious hazard condition. In some embodiments, the thresholds thathazard detector 104 uses when determining whether a serious hazardcondition exists are set to or at least based on UL standards. Hushingone alarm may, but typically does not, affect other operations of hazarddetector 104 such as further monitoring, annunciation of other alarms,broadcasting alarm status to other devices of the smart-homeenvironment, and/or requests routed through a smart thermostat to alteroperation of home systems such as HVAC heaters and fans, to try to stopa source of a hazard or determine a cause of a hazard.

According to embodiments, pre-alarms indicating pre-hazardous conditionsprovide details about the pre-hazardous condition. For example, hazarddetector 104 and/or the central server and cloud-computer system 164 maysend a message to the computer 166 of user stating specifics about thecondition. In one particular example, the message states, “The CO levelin your home has increased twenty-percent in the last two weeks. Youmight consider having an expert inspect your home to determine thecause.” Also for example, hazard detector 104 and/or other smart devicesin the home may make similar audible announcements or display similarwritten messages (e.g. via a user interface or projection onto a wall orceiling).

Pre-Alarm Settings Automatically Set Based on Location

According to embodiments, thresholds (e.g., smoke thresholds, COthresholds, heat thresholds) used by hazard detector 104 to determinewhether an alarm condition, such as a pre-hazardous condition or aserious hazard condition, exists are adjusted or set based at least inpart on where the hazard detector 104 is located. For example, thethresholds used by a hazard detector 104 located in a kitchen to detectalarm conditions in the kitchen may be different than the thresholdsused to by a hazard detector 104 located in a bedroom to detect alarmconditions in the bedroom. Thresholds used by the hazard detector 104located in the kitchen account for smoke levels common to kitchens,thereby making the hazard detector 104 less sensitive to smoke resultingfrom normal cooking activities that occur in kitchens, thus less likelyto false alarm. Reducing false alarms is one notable advantage providedby adjusting or setting thresholds based on where hazard detector 104 islocated. Reducing false alarms reduces the likelihood of usersdisconnecting, unplugging, or otherwise disabling hazard detectors dueto the inconvenience and annoyance of false alarms. Accordingly, byadjusting or setting thresholds to reduce false alarms, hazard detector104 may save the lives of those who would otherwise disable their hazarddetectors.

Turing to FIG. 16, a flow diagram is provided of an exemplary method2400 of setting one or more thresholds used by a hazard detector (e.g.,hazard detector 104) to determine whether a pre-alarm condition exists,according to an embodiment. According to embodiments, the thresholds areset based on the hazard detector 104's location within a home. Asindicated at step 2405, the method 2400 generally begins with hazarddetector 104 receiving location information. In the illustrated example,hazard detector 104 receives location information from a user. Forexample, a user provides hazard detector 104 with user input thatindicates the location of hazard detector 104 within the home orstructure. According to embodiments, the user input indicates the nameor type of the room or area (e.g., bedroom, kitchen, etc.) where hazarddetector 104 is located.

For example, in step 2405 a user may operate application 1414 (see FIGS.7-11) running on mobile computing device 1416 and providing a userinterface that allows a user to input a location for hazard detector104. To do so, the user selects a room types (e.g., Living Room, MasterBedroom, etc.), optionally from a list. More particularly, the user mayperform a slide gesture on a list object causing the list of room typesincluded on the list object to scroll up or down and place one of theroom types in a select field. The user may select a done button tosubmit the user input, thus indicating the location of the hazarddetector within the home. The mobile computing device 1416 would thentransmit the user input to hazard detector 104. In some embodiments, themobile computing device 1416 transmits the user input directly to hazarddetector 104 via a personal area network (PAN), short-range wirelesscommunication (e.g., BLUETOOTH, NFC), a local area network (LAN), etc.In other embodiments, the mobile computing device 1416 transmits theinput over the Internet to the server 164, which updates the user'sonline management account to include the location information for theparticular hazard detector 104. It should be appreciated that theseembodiments of step 2405 are merely examples and that locationinformation may be inputted to hazard detector 104 according to anymeans know to those have ordinary skill in the art. Further, it shouldbe appreciated the location information could be stored locally byhazard detector 104 and/or remotely on a user's online managementaccount.

As indicated at step 2410, the method 2400 further involves accessingpredetermined thresholds that correspond to the location of hazarddetector 104. According to embodiments, data is provided that includespredetermined thresholds that hazard detector 104 uses to set itsthresholds, which it uses to determine whether pre-alarm conditions forsmoke, CO, and heat exist in the location where it is installed. Thepredetermined thresholds vary based on location. For example, thresholdsfor determining that a pre-alarm condition for smoke exists in theliving room may be less than the thresholds for determining that apre-alarm condition for smoke exists in the kitchen. Thus, the hazarddetector in the kitchen would be less sensitive to smoke and istherefore less likely to activate a false pre-alarm.

Exemplary predetermined, pre-alarm thresholds are provided in data table2500 of FIG. 17. As illustrated, data table 2500 includes columns 2510,2515, 2520, and 2525. The “Room Type” column 2510 lists variouslocations within a home, including living room, bedroom, garage, laundryroom, and kitchen. It should be appreciated that these locations areprovided for illustrative purposes and that other locations may beprovided in addition to or in place of the illustrated locations. The“Pre-alarm Condition for Smoke Thresholds” column 2515 listspredetermined thresholds for determining whether a pre-alarm conditionfor smoke exists, the “Pre-alarm Condition for CO Thresholds” column2520 lists predetermined thresholds for determining whether a pre-alarmcondition for CO exists, and the “Pre-alarm Condition for HeatThresholds” column 2525 lists predetermined thresholds for determiningwhether a pre-alarm condition for heat exists.

As indicated by the data in column 2515 of table 2500, the predeterminedthreshold for determining whether a pre-alarm condition for smoke existsin a living room is “Obscuration>=“0.5” continuously for 30 s”. Thus, ahazard detector 104 that receives user input indicating that it islocated in a “living room” sets its thresholds for detecting a pre-alarmcondition for smoke to “Obscuration>=“0.5” continuously for 30 s”.Further, according to the example data provided in columns 2520 and2525, a hazard detector 104 that is located in the living room will setits thresholds for detecting a pre-alarm condition for CO to “CO>=“100”instantaneously after 5 min of monitoring”, and will set its thresholdsfor detecting a pre-alarm condition for heat to “Temp>=“90” ANDTCPM*>=“12””.

On the other hand, as also indicated by the data in column 2515 of table2500, the predetermined thresholds for determining whether a pre-alarmcondition for smoke exists in the kitchen are “Obscuration>=“2.5”continuously for 1 min AND Humidity<humidity from 3 mins ago”. Thus, ahazard detector 104 that receives user input indicating that it islocated in a “kitchen” will set its thresholds for detecting a pre-alarmcondition for smoke to “Obscuration>=“2.5” continuously for 1 min ANDHumidity<humidity from 3 mins ago”. As such, a hazard detector locatedin a kitchen will be less sensitive to smoke than a hazard detectorlocated in a living room. In particular, a hazard detector in a livingroom will determine that a pre-alarm condition for smoke exists when itdetects smoke obscuration above “0.5” for thirty seconds, whereas ahazard detector in a kitchen will not determine that a pre-alarmcondition for smoke exists until it detects smoke obscuration above“2.5” for one minute and that humidity has decreased in the last threeminutes. Accordingly, a hazard detector in a kitchen is less likely togenerate a false pre-alarm when a small amount of smoke is emitted fromthe oven, stovetop, microwave, etc. Further, a hazard detector locatedin a kitchen is less likely to mistake steam from boiling water assmoke, since its thresholds for determining a pre-alarm condition forsmoke require that humidity in the room decrease.

According to embodiments, data having predetermined thresholds andcorresponding locations, such as illustrated in FIG. 17, is storedlocally on hazard detector 104. For example, the data may be a lookuptable stored in memory on the hazard detector 104. Thus, to accesspredetermined thresholds, according to step 2410, hazard detector 104accesses the lookup table stored in local memory. In other embodiments,predetermined thresholds may be stored on a remote server, such as thecentral server or cloud-computing system 164. According to theseembodiments, a hazard detector 104 obtains the predetermined pre-alarmthreshold by receiving the predetermined pre-alarm threshold from aserver via a network communication. For example, hazard detector 104 maytransmit a query message that includes the room type inputted by theuser, via a network connection, to a server (e.g., server 164). Uponreceiving the query message, the server accesses data (e.g., data table2500) having room types and corresponding predetermined pre-alarmthresholds to identify the predetermined pre-alarm thresholds thatcorrespond to the room type. The server includes the identifiedpredetermined pre-alarm thresholds in a response message and sends thatmessage back to the hazard detector. The hazard detector 104 receives,via the network connection from the server, a response message thatincludes the predetermined pre-alarm threshold that corresponds to theroom type.

Upon accessing data having predetermined thresholds and correspondinglocations according to step 2410, method 2400 proceeds to step 2415 foridentifying in the accessed data the predetermined thresholds thatcorrespond to the location information. According to an embodiment, withreference to table 2500 of FIG. 17, this step involves identifying thethresholds listed in columns 2515, 2520, and 2525 that correspond withthe inputted room type of column 2510. In one particular example withreference to table 2500, if the user input indicates that hazarddetector 104 is located in a laundry room, then the correspondingthresholds of column 2515 for determining a pre-alarm condition forsmoke are “Obscuration>=1.5 continuously for 1 min OR Temp>+10 in lastmin”, the corresponding thresholds of column 2520 for determining apre-alarm condition for CO are “CO>=200 instantaneously after 5 min ofmonitoring”, and the corresponding thresholds of column 2525 fordetermining a pre-alarm condition for heat are “Temp>=110 ANDTCPM*>=15”. It should be appreciated that the predetermined thresholdsof table 2500 are merely examples for illustrative purposes.

Referring again to FIG. 16, method 2400 proceeds to step 2420 forsetting the hazard detector's thresholds equal to the identifiedpredetermined thresholds that correspond to the location of hazarddetector 104. According to embodiments, hazard detector 104 sets therespective thresholds it uses to detect pre-alarm conditions for smoke,CO, and heat equal to the corresponding predetermined thresholdsidentified according to step 2415.

Adjusting Pre-Alarms Based on User Preferences, History, and OtherEnvironmental Variations, e.g., for CO Detector Installed in Garage

According to embodiments, hazard detector 104 is configured toautomatically create a dynamically adjustable pre-alarm based onhistorical CO data to detect a pre-alarm condition involving CO in agarage, even if hazard detector 104 is not located in the garage. COdetectors are typically not recommended for garages because of the highfrequency of false alarms due to the high levels of CO produced by cars.However, it would be beneficial to provide CO detection for garages. Forexample, the smart-home environment can learn what CO levels are typicalfor a garage and thus infer when atypical CO events occur. For example,in the event a user slips and falls after starting their car, an alarmto another user that indicates an alarm condition involving CO isoccurring in the garage may save that user's life.

To provide said CO-detection for garages, hazard detector 104 records ahistorical log of CO data that it has detected. This log may be storedlocally on hazard detector itself, or it may be stored at server 164,and the data therein may be analyzed to provide a variety of inferencesabout how CO levels vary in a particular garage. For example, aprocessor of hazard detector 104 or of server 164 can apply algorithmsto the logged CO data to determine whether the data indicates that oneor more automobiles are regularly started nearby. The algorithms maydetect occasional CO spikes that quickly dissipate and, based on theamount by which the CO level increases and the amount of time it takesfor the detected CO to dissipate, hazard detector 104 or server 164 mayinfer that the spike was caused by a car that was started and thendriven away. Appropriate, multiple thresholds may be developed forhazard detectors 104 that are in or near intermittent CO sources, suchas kitchens (with CO released from gas stoves, and/or from cooking),basements (combustion based heat sources), garages (motor vehicles, lawnmowers and other combustion based motors); methods for developing andimplementing such multiple thresholds are discussed below in connectionwith FIGS. 20D and 20E.

If, after making an inference that a car is regularly started and drivenaway, hazard detector 104 observes an incident where the CO spikes butdoes not dissipate in a manner that is consistent with previous COspikes, then hazard detector 104 may determine that a pre-hazardcondition for CO exists. Because it takes advantage of historical data,this determination can be reached with confidence even if the increasedCO levels are not high enough to present a serious hazard, or even apre-hazardous condition under usual circumstances. For example, COthresholds for pre-hazardous and serious hazard conditions may require ahigh CO concentration level for a one-hour period before alarming, or amoderately high CO level for one month before alarming.

Adjusting Pre-Alarm Thresholds and Volume if Someone is Sleeping

Tragically, people sometimes die in house fires because they aresleeping and do not hear an alarm in time to evacuate to take remedialmeasures to put out the fire. Accordingly, hazard detector 104 iscapable of adjusting the thresholds it uses for determining whether apre-alarm condition exists so that it “pre-alarms” sooner and morefrequently. Further, hazard detector 104 is capable of increasing thevolume of its alarm when it determines that an individual is sleeping inthe home.

According to embodiments, to determine when an occupant is sleeping in aparticular room, hazard detector 104 leverages sensors of smart deviceslocated in the mesh network of the smart-home environment in combinationwith rules-based inference engines or artificial intelligence providedat the central server or cloud-computing system 164. According toembodiments, the smart device in the smart-home environment 100 thathappens to be closest to an occupant when that occupant falls asleep maytransmit a message indicating that the occupant has stopped moving andappears to be sleeping. The message will be transmitted through the meshnetwork to the hazard detectors 104, which will then automaticallyincrease their alarm volumes and reduce the thresholds used to determinewhether pre-hazardous conditions exist in the home. Thus, in the eventof a potentially dangerous condition, the hazard detectors 104 mayprovide an alarm sooner and louder than usual, thereby making it morelikely that the occupant will already be awake by the time theconditions worsen enough to warrant an alarm indicating a serious hazardcondition (e.g., an alarm based on UL standards).

Simple Alarm Flow; Announcement that “Hazard is Clearing”

FIG. 18A illustrates a method 2600 for providing an alarm message whenan alarm condition is detected in a location and providing a “hazard isclearing” message as the alarm condition clears from the location,according to embodiments. Oftentimes, after receiving an alarmindicating that an alarm condition has been detected in their home,users evacuate the home and/or take remedial measures to clear the alarmcondition. For example, upon hearing a smoke alarm, users may search thehome to find the source of the smoke and take remedial measures to stopthe smoke, such as by turning off a smoking oven or stove. However,known hazard detectors do not notify users when the condition has beenaddressed such that the hazard is at least beginning to clear. This isparticularly true for CO alarms. In response to a CO alarm, users mayopen windows to clear CO from the home, but, because humans cannot senseCO, they cannot determine if the CO condition is clearing. Accordingly,hazard detector 104, such as by implementing method 2600, continuesmonitoring after it provides an alarm and, if it detects that thecondition is clearing, it communicates to users a “hazard is clearing”message that informs users that the condition is clearing.

The method 2600 generally begins at step 2605 where hazard detector 104receives location information. This step is similar to step 2405 ofmethod 2400 and step 1320 of method 1300. As described herein withreference to those methods, in step 2605 a user provides hazard detector104 with user input that indicates the location of hazard detector 104within the home or structure. According to embodiments, the user inputindicates the name or type of the room or area where hazard detector 104is located. The room names or types inputted by users include, forexample, Master Bedroom, Kids Bedroom, Guest Bedroom, Kitchen, LaundryRoom, Garage, Living Room, Den, Office, etc. In step 2610, method 2600monitors the location for an alarm condition, such as the alarmconditions for smoke, CO, and heat described above.

As indicated at step 2615, upon detecting an alarm condition, hazarddetector 104 provides an alarm message notifying users of the detectedcondition. It should be appreciated that the alarm message may becommunicated to users via multiple channels, such as broadcast byspeaker, changes to emitted light color, intensity and/or dynamics,and/or distribution by electronic message (e.g., SMS, e-mail, alert in asmartphone or tablet app). Further, according to embodiments, the alarmmessage includes a description of the detected condition and a locationwhere the condition was detected. For example, hazard detector 104 usesits speaker 950 to output a voice announcement that includes adescription of the condition and a location where the condition has beendetected. In other examples, hazard detector 104 causes a correspondingelectronic message (e.g., e-mail, SMS) to be sent to computers 166 ofusers associated with the home. According to embodiments, hazarddetector 104 determines the location based on the room name or typeprovided by the user, as previously described with reference to step2605. The hazard detector includes this room name or room type in alarmmessages to indicate where a condition has been detected. Further,according to examples, hazard detector 104 is at least capable ofdetecting the alarm conditions described above with reference to FIGS.16 and 17, including for example alarm conditions for smoke, CO, andheat.

In a particular example, upon detecting an alarm condition for smoke ina kitchen, hazard detector 104 provides the alarm “Smoke detected inkitchen”. Hazard detector 104 can announce the “Smoke detected inkitchen” alarm via its speaker 950 and/or it can send the “Smokedetected in kitchen” via electronic messages to computers 166. Otherexample, announcements include, “Smoke detected in living room”, “Smokedetected in Master Bedroom”, “Smoke detected in kid's bedroom”, “Smokedetected in guest bedroom”, etc.

After detecting the alarm condition and communicating to users acorresponding alarm message, hazard detector 104 continues to monitorthe location where it is installed, as indicated at step 2620. At step2625, if the alarm condition continues to be detected or if a new alarmcondition is detected, hazard detector 104 may provide an alarm messageindicating the continuing and/or newly detected condition, as indicatedat step 2625. In particular, if the previously detected conditionpersists, hazard detector 104 continues to provide the same alarmmessage. However, according to embodiments, if the condition hasescalated or improved, hazard detector 104 alters the alarm message toreflect the changed condition.

If the condition has escalated from a pre-hazardous condition to aserious hazard condition, hazard detector 104 indicates this escalationin its alarm message. For example, rather than announcing “Smokedetected in living room”, hazard detector alarms according to ULstandards for smoke, and includes an announcement that the condition isserious. For example, this serious hazardous alarm may be “BEEP, BEEP,BEEP—Smoke detected in living room—BEEP BEEP BEEP!” On the other hand,if the condition has improved and gone from a serious hazard conditionto a pre-hazardous condition, hazard detector 104 indicates thisimprovement in its alarm message. For example, rather than announcingalarming according to UL standards and including “BEEPS” in the message,the hazard detector 104 may simply announce “Smoke detected in livingroom”. According to embodiments, hazard detector 104 may explicitlyindicate that the condition has improved or worsened. For example, thealarm message could say, “Condition has escalated to a serious hazardcondition” or “Condition has improved, but a pre-hazardous conditionstill exists”.

Still referring to step 2625, if the detected alarm condition hascleared such that no alarm condition is detected, hazard detector 104may communicates to users a “hazard is clearing” message, as indicatedat step 2630. In embodiments, the “hazard is clearing” message does notspecify or guarantee that normalcy with respect to the detectedcondition has been restored. For example, if the detector condition weresmoke, then the “hazard is clearing” message is limited to smoke in thekitchen and it may be audible communicated to users as, “The previouslydetected smoke in the kitchen is clearing.” Referring to the examplealarm condition for smoke in a kitchen mentioned above, if uponcontinued monitoring of the kitchen, hazard detector 104 determines thatthe alarm condition is clearing, then hazard detector 104 maycommunicate a corresponding message. For example, hazard detector 104may provide the message, “Smoke in the kitchen is clearing”. Hazarddetector 104 can announce the “Smoke in the kitchen is clearing” messagevia its speaker 950 and/or via electronic messages to computers 166.Continuing with this example, if other hazard detectors 104 in the homehad also detected and alarmed for alarm conditions, those hazarddetectors 104 can provide their own “hazard is clearing” messages whenalarm conditions in the locations have cleared. For example, upon alarmconditions clearing in its location, hazard detector 104 located in theliving room can announce, “Hazard is clearing in the living room”.Similarly, hazard detector 104 in the master bedroom announces, “Hazardis clearing in the master bedroom”, and so forth. This way, as thehazard clears in the various rooms of the house, the user will receivemessages, such as audible voice announcements from the hazard detectorsthemselves, and/or electronic messages sent to users' computers 166.These “hazard is clearing” alarms are particularly useful for alarmconditions involving CO, because humans cannot sense CO.

Alarm Implementation: Status Identifiers, Alarm Broadcasts, and AudibleAlarms

FIG. 18B illustrates a method 2650 for assigning and broadcasting alarmstatus identifiers in a smart device, according to embodiments. Method2650 includes exemplary action and decision steps that utilize statusidentifiers to define alarm states; it should be apparent upon readingand understanding the disclosure herein that alarm states are not theonly type of states that may be defined by status identifiers. Moreover,although method 2650 is presented in terms of alarms related to CO, itshould be apparent that method 2650 may be adapted for use withdetection of other smart-home environment characteristics such ashazardous substances, extreme temperatures, and/or other conditions ordetectable substances that indicate a hazardous condition, such assmoke.

Method 2650 begins with a step 2652 of measuring CO in a location of aparticular hazard detector 104. Step 2654 assesses each applicable alarmcondition for the particular hazard detector 104; there may be one ormore such limits that depend on the most recent CO measurement, COhistory at the location of the hazard detector, current measurements ofother smart-home environment characteristics and other factors. Eachalarm condition typically has three possible alarm states: No hazard, apre-hazardous condition, or a hazardous condition. The default conditionis no hazard; possible criteria and thresholds for determining if apre-hazardous or hazardous condition are disclosed elsewhere herein. Ifstep 2654 determines that a CO measurement of an alarm condition doesnot meet either of an applicable pre-hazardous or hazardous threshold,an alarm status identifier for that alarm condition is set to zero instep 2656. If step 2654 determines that the CO measurement meets orexceeds an applicable pre-hazardous threshold but does not meet ahazardous threshold, the alarm status identifier for that alarmcondition is set to one in step 2658. If step 2654 determines that theCO measurement meets or exceeds a hazardous threshold, the alarm statusidentifier for that alarm condition is set to two in step 2660. Afterthe applicable step 2656, 2658 or 2660, step 2662 broadcasts theidentity of the hazard detector 104 and the determined alarm statusidentifier to other smart devices. This allows other smart devices torepeat audible warnings about pre-hazardous or hazardous conditions inany location of the smart-home environment. A subsequent step 2664checks to see if any further alarm conditions need to be assessed; ifso, method 2650 returns to step 2654, otherwise method 2650 returns tostep 2652, repeating indefinitely.

Turning on HVAC Fan to Clear Smoke and/or CO

According to an embodiment, in the event of an alarm condition involvingsmoke, CO, or heat in the home, an HVAC fan can be turned on to helpremedy the alarm condition by at least partially removing the smoke, CO,or heat from the home, or at least moving air to the most severelyaffected home areas. FIG. 19 provides a method 2700 that can beimplemented in a home having a smart thermostat 102 that communicateswith a hazard detector 104 to control the HVAC fan to help remedy alarmconditions detected by the hazard detector, according to embodiments.

Method 2700 generally begins at step 2705, where an alarm condition inthe home is detected. For example, one or more hazard detectors 104 in ahome detect an alarm condition, such as a pre-hazardous or serioushazard condition involving smoke, CO, or heat. As indicated at step2710, upon detecting an alarm condition, the smart thermostat and thehazard detector 104 coordinate to test whether the HVAC fan helps remedythe detected condition. For example, the smart thermostat 102 turns onthe HVAC fan and the hazard detector 104 monitors the home environmentto determine if the detected alarm condition begins to improve, at leastin the area of the specific hazard detector 104. For example, if thealarm condition is a pre-hazardous condition for smoke or CO in theliving room, the hazard detector 104 determines whether the smoke leveldecreases in the living room. Further, to make sure the HVAC is not justredistributing smoke throughout the home, the hazard detector 104 maycommunicate with other hazard detectors 104 in the home to make sure thesmoke or CO level in other rooms is not increasing. It determines thatthe HVAC fan helps remedy the alarm condition, if the smoke leveldecreases throughout the house. However, if the smoke or CO is justredistributed to other rooms, then it determines that the HVAC does notimprove the condition. Interconnected hazard detectors throughout thehome make this possible. Similarly, for example, if the alarm conditionis a pre-hazardous condition for CO in the living room, the hazarddetector 104 determines whether turning on the HVAC fan causes the COlevel to decrease in the living room. Distributing CO throughout thehouse could be potentially harmful, but could also help bring down a COlevel in a severely affected room from a lethal level. Accordingly, thehazard detectors monitor the CO levels in other rooms to ensure thatturning on the HVAC fan to reduce CO in the living room either does notincrease CO levels in other rooms, or that any such increases are modestcompared to reducing an extremely high CO level in one or more rooms.

As indicated at decision step 2725, if turning on the HVAC fan indeedhelps remedy the alarm condition by at least partially removing smoke,CO, or heat from the home, then as indicated at step 2730 the thermostat102 continues to run the HVAC fan. For example, the thermostat 102 runsthe HVAC fan until the hazard detectors determine that the condition isameliorated or until the condition is no longer continuing to improve(e.g., the smoke level is no longer decreasing). Further, as indicatedat step 2735, the thermostat 102 updates the account settings, such asin the online management account discussed with reference to FIGS. 13and 15, that turning on the fan when the alarm condition is detectedhelps remedy the alarm condition. Thus, according to an embodiment, thenext time the alarm condition is detected, the HVAC fan is automaticallyturned on, without testing to determine whether the HVAC fan helpsimprove the condition.

Referring again to decision step 2725, if turning on the HVAC fan doesnot help remedy the alarm condition, then as indicated at step 2735, thethermostat 102 updates the account settings to indicate that turning onthe fan does not help ameliorate the alarm condition. Thus, the nexttime the alarm condition is detected, the HVAC fan is not turned on.

Determining Cause of CO Condition

Oftentimes, in the event an alarm condition involving CO is occurring ina home, the source of the CO is a thermostat-controlled, combustionbased heat source, such as a gas or heating oil burning HVAC systemthat, due to an improperly vented furnace or boiler, emits CO into thehome as a byproduct of creating heat. However, thermostat-controlledheating sources are not always the source of the CO. For example, highCO levels in homes may also be caused by non-thermostat-controlledheating sources, such as fireplaces, wood stoves, kerosene heaters, etc.Further, high CO levels may be caused by non-heating HVAC sources, suchas gas water heaters, gas stoves and ovens, generators and otherfossil-fuel-powered (e.g., gasoline, kerosene, propane, natural gas,etc.) equipment.

FIG. 20A is a flowchart of a method 2800 for determining a source of COin a home environment in which an alarm CO condition has been detectedand, when appropriate, altering at least one aspect of the homeenvironment to at least partially ameliorate the alarm CO condition,according to embodiments. Method 2800 may be performed, for example, bysmart hazard detector 104 in cooperation with smart thermostat 102,which include CO measurement hardware and the ability to control aheater (e.g., HVAC system 103) respectively. However, it should beunderstood that determinations and inferences based on the COmeasurements may be performed by other devices as well; for example, COmeasurements may be transmitted to central and/or offsite computersystems, such as cloud-computing system 164 (FIG. 1) for analysis bysuch systems. A system that performs data analysis related to COmeasurements may be referred to herein as the “analyzing system” withthe understanding that such system may be any of the hazard detector104, smart thermostat 102, cloud-computing system 164 or other computingsystem that can access the required data.

As indicated at step 2802, method 2800 generally begins with detectingan alarm condition for CO in the home. In the context of method 2800,“alarm condition” can mean either of a serious hazard “alarm” condition,or a “pre-alarm” condition, that is, method 2800 may be performed todetermine a source of CO whether the condition detected is strictlydefined as a “hazard” or it is merely out of the ordinary. Upondetecting the alarm condition, method 2800 accesses a memory of smartthermostat 102, as indicated at step 2805. In a first decision step2807, information from the memory of smart thermostat 102 is used todetermine whether a heater of an HVAC system being controlled by smartthermostat 102 uses a fossil fuel-based heat source. If step 2807determines that the heater is not fossil-fuel based (e.g., it is insteadan electric heater, heat pump or hydrogen burning heater) method 2800skips directly to step 2845, described below. If step 2807 determinesthat the heater is fossil fuel-based, method 2800 proceeds instead tostep 2810.

At decision step 2810, smart thermostat 102 determines whether thethermostat-controlled heater is running. As indicated at step 2815, ifthe thermostat-controlled heater is running, then the smart thermostat102 turns off the heater. At indicated at step 2820, after the heater isturned off, hazard detector 104 monitors the home environment to assesswhether the CO condition is improving (e.g. CO level decreasing). Asindicated at step 2825, if the CO condition improved, the smartthermostat 102 does a “pattern matching” test by turning the heater backon and, as indicated at step 2830, the hazard detector assesses whetherthe CO condition is worsening now that the heater has been turned backon. As indicated at step 2835, if the condition worsened when the heaterwas turned on again, then an inference is made that thethermostat-controlled heater is the source of the CO condition in thehome environment. As indicated at step 2840, if the CO condition isabove a threshold level, the smart thermostat 102 turns off the heater.For example, smart thermostat 102 may turn off the heater if the COcondition is determined to be a serious hazard condition. As indicatedat an optional step 2845, a user may be notified that thethermostat-controlled heater is likely the source of the CO condition.Step 2845 may or may not be performed in every instance of method 2800;for example, if the alarm condition detected in step 2805 is a COexcursion from a statistical baseline in which a CO level is elevatedbut is still far from dangerous levels.

Referring again to step 2810, if—after detecting the CO condition—it isdetermined that the thermostat-controlled heater is not on, the hazarddetector 104 monitors the home environment to determine whether the COcondition is worsening. For example, the hazard detector ‘watches’ theCO level to ‘see’ if it is staying the same, getting better, or gettingworse. As indicated at step 2860, if the condition is not worsening(i.e., staying the same or getting better), then the smart thermostatengages in the “pattern matching” described above with reference tosteps 2825 to 2835, where it “looks” for a pattern where COconcentration increases when heater is on and decreases when heater isoff. If it “sees” that pattern, then it infers that the heater is thesource of the CO. However, as indicated step 2865, if the condition isworsening, even though the thermostat-controlled heater is off, thesmart thermostat 102 monitors temperature of the home environment todetermine if the temperature is stable or increasing. As indicated atstep 2870, if the temperature is stable or increasing, even though thethermostat-controlled heater is off, then it may be inferred thatanother heat source (e.g., fireplace, wood stove) is heating the homeand that that heat source is the cause of the CO condition. The user maythen be notified that a non-thermostat-controlled heater, such as afireplace, is the likely source of the CO, as indicated at optional step2845. However, as indicated at step 2875, if the temperature is notstable or increasing (i.e., the temperature is decreasing), then it isinferred that a non-heat source (e.g., hot water heater, gas oven orstove, etc.) is the cause of the CO condition and the user may benotified accordingly, as indicated at optional step 2845.

According to embodiments, hazard detector 104, other smart devices ofsmart-home environment 100, cloud-computing system 164 or other systemsthat receive data from smart-home environment 100, can determinepre-hazardous alarm thresholds to avoid nuisance alarms and/or makeinferences about routine CO excursions, including the source(s) of suchexcursions. In embodiments, these determinations and/or inferences mayoccur even in the event the home environment does not include anetwork-connected smart thermostat 102 that controls the home's climatecontrol system. For example, hazard detector 104, other smart devices orcloud based systems can ‘look’ for patterns involving temperature in thehome and CO level in the home, and can set appropriate CO pre-alarmthreshold(s) accordingly. If CO increases when temperature increases andif CO decreases when temperature decreases, then a hazard detector 104may infer that a heater of some kind inside the home is the source ofthe CO and notify a user regarding the same. Alternatively, if COroutinely increases at one or more times of day without a concurrenttemperature increase, the analyzing system may not be able to determinea source, but may be able to establish higher pre-hazardous conditionlimits for those times of day. Or, if CO increases can be correlatedwith other household events (e.g., noise in the kitchen, indicating thatcooking is taking place, or a sequence of garage door openings and/orclosings) the analyzing system may be able to establish higherpre-hazardous condition limits that can be applied in association withsuch events (see FIG. 20E).

Similarly, in embodiments, a smart thermostat can, alone or coordinatedwith a smart hazard detector, operate any controllable aspect of anassociated climate control or HVAC system in isolation, to determine asource of a hazard or to ameliorate a hazard that exists. For example,it may be known (e.g., at installation time of the smart thermostat) orcan be determined (see FIG. 20A) that a climate control system includesa combustion based heat source. With this knowledge, the smartthermostat may be able to send independent signals to differentcomponents of the climate control system such as a system fan and theheat source. For example, it may be very useful to turn off the heatsource (to shut down a CO source) while leaving a system fan running (tohelp clear CO from the home, or at least reduce the CO from lethallevels in one particular area). It may also be possible, or it may bethe only available option, to send a single signal that causes theclimate control system to sequentially turn off the heat source first,and later shut off a system fan.

FIG. 20B is a flowchart illustrating a method 2900 for determining oneor more sources of CO in a smart-home environment. In a first step 2910,a smart device of the smart-home environment measures a level of CO togenerate a CO measurement. It should be understood that a CO“measurement” as referred to here may be a single point, or a trend ofsuch measurements (e.g., wherein at least the two or more most recentmeasurements increase in succession over a defined set of previousmeasurements). An example of step 2910 is one of hazard detectors 104generating a CO measurement. Other smart devices of the smart-homeenvironment generate current characteristics of the smart-homeenvironment; these characteristics may be measurements (e.g.,temperature, smoke, other CO measurements, sounds, light, detectedmotion and the like), settings (e.g., temperature settings, controlstates of HVAC equipment and the like) or inferences (such as whetherusers or occupants of the smart-home environment are “home,” “away,”“sleeping” and the like, as described elsewhere herein). In step 2915,the CO measurement and the current characteristics are provided to ananalyzing device. The analyzing device may itself be the hazard detector104 that measured the CO, another smart device of the smart-home system,a computer associated with the smart-home environment (e.g. a computer166 in the form of a computer, a smartphone, a tablet or the like) or itmay be a cloud based computer system, such as cloud-computing system164, FIG. 1.

In step 2920, the analyzing device evaluates a set of correlationscenarios, each of which attempts to attribute CO to a specific source.Each correlation scenario, when evaluated, yields a result state thatmay yield a positive or negative result state in an optional substep2925, (e.g., “yes” the CO is coming from the specific source or “no” itis not); or a variable result in an optional substep 2930 that indicatesa conclusion that the specific source “might be” where the CO is comingfrom, with a degree of confidence associated with the result. Inembodiments, the result of evaluating each correlation scenariogenerates a confidence metric that the CO is from the specific source.When the evaluation generates a positive or negative result state, afixed value may be assigned to the result state, while if the evaluationgenerates a variable result, a variable value may be assigned as theconfidence metric. This allows inferences to be built up by aggregatinga series of results that would be of low overall confidence valueindividually, but add to form a high confidence value when all of theresults point to the same conclusion. It is noted for completeness thatconfidence metrics may be arbitrarily assigned as estimated percentageconfidence of a particular result, but that the percentages so assignedmay not add up to 100%.

In step 2940, the analyzing device selects one or more of the specificsources as the most likely CO source, by aggregating results of thecorrelation scenarios. For example, in a first optional substep 2945,the analyzing device may sum confidence metrics for each of the specificsources that were evaluated in correlation scenarios. Step 2940 mayalso, in an optional substep 2950, determine that one of the specificsources is more likely than all of the others. For example, a confidencewindow may be established, and the results of step 2940 may be based onwhether one, two or more of the specific sources have confidence metricswithin the confidence window of one another. To illustrate, if severalscenarios are evaluated and one specific source has a confidence metricsum of 56% while no other source has a confidence metric sum greaterthan 10%, method 2900 may “conclude” that the specific source with the56% confidence metric sum is the CO source, and may make announcementsand/or action decisions (such as operating HVAC controls, etc. asdiscussed in connection with FIG. 20A and elsewhere) based on this“conclusion.” Alternatively, in another optional substep 2955, step 2940may determine two or more specific sources have confidence metric sumswithin a predetermined tolerance of the highest such sum, and maydetermine that those sources that are both possible sources of the CO.To illustrate, if the confidence window is established as 10%, and threespecific causes evaluated in step 2920 generate confidence metric sumsof 40%, 35% and 18%, method 2900 may conclude that the first twoconfidence metric sums indicate two specific sources, either of whichcould be the CO source, while the third specific source could not.

FIG. 20C shows a table 2980 illustrating possible correlation scenariosfor identifying CO sources. Each row of table 2980 shows a correlationscenario including a CO measurement whose source may be identified,other smart-home characteristic(s) that may help identify the source, asource identified as correlating with the CO measurement and thesmart-home characteristic(s), and a possible confidence metric thatcould be assigned to the identification. Table 2980 is exemplary only,and merely provides some examples of correlation scenarios that could bedeveloped. Many other causes could be correlated to CO measurements andsmart-home characteristics; the confidence metrics are also exemplaryand would be adjusted for a given smart-home environment based oninformation acquired from that particular environment. A table similarto table 2980 could be set up, maintained by and made available to oneor more analyzing devices in a smart-home environment such that thescenarios therein could be evaluated. The evaluation of correlationscenarios could be continuous or set up to occur on demand based onlocation associated with a CO measurement, or based on a CO measurementexceeding a typically low threshold that indicates a small excursionabove a typical level.

Inferences about CO sources can also be made based on user statusinformation, that may be provided by the user, or inferred. For example,any sharp increase in CO when the smart-home environment is in an “away”or “vacation” state may be treated as indicating at least a seriousmalfunction in a heating system or other combustion based system, orpossibly a fire. Responses to such sharp increases when occupants arebelieved to be “away” may trigger earlier and sharper warnings bothwithin the smart-home environment in case, unknown to the smart-homeenvironment someone is at home, and is unaware of the CO source. Alertsmay also be made earlier to systems that are or may be physicallyoutside the smart-home environment. For example, alerts may be sent tocomputers 166 that are mobile devices, or to cloud-computing system 164,which may interface with alarm companies, law enforcement and/orfirefighting organizations. Similarly, when an occupant is believed tobe at home but sleeping, alerts may be generated at lower CO levelsand/or directed to an area in which the occupant is believed to be.

Successive observations can be utilized to refine and increaseconfidence in correlation scenarios, and thus to increase the confidencemetric assignable to such scenarios. Such successive observations mayvalidate some or all the circumstances of each correlation; for example,a phenomenon that initially appears to occur every day may not continueto do so, yet may be discernible as occurring on weekdays but notweekends, or on some other recognizable subset of days. Such subsets maybe recognizable as, for example, every other day, every third day, onceor twice a week, weekend days, the first and third Mondays of eachmonth, every weekday except during summer, and the like. Correlationscenarios can be refined over time to best match the sensedcharacteristics of each smart-home environment, and the confidencemetrics assigned in connection with evaluating the correlation scenarioscan be increased (or decreased) according to the degree to which suchcharacteristics always match, or do not match, specific instances. Anyof the devices of the smart-home network itself, and/or externalresources such as computer 166 or cloud-computing system 164, mayexamine past data to find and refine correlations. Possible results ofsuch examination include adjustments to the confidence metricsassociated with one or more correlation scenarios, new entries to table2980, and/or splitting existing correlation scenarios into two or morecorrelation scenarios that better track different combinations of COmeasurements and smart-home characteristics.

Some smart thermostats provide extreme temperature safeguards in orderto keep pipes from freezing at very low outside temperatures, or preventpet deaths at very high outside temperatures. Such thermostats may have,for example, low (or high) temperature safety thresholds that ifcrossed, cause the thermostat to attempt to activate heating at lowtemperature, or cooling at high temperature. Embodiments herein mayhonor the extreme temperature safeguards even when doing so overrules COrelated detection and climate control system operational conditionsdescribed herein. For example, a smart thermostat may first operateunder a rule that turns off an HVAC heat source because of dangerous COlevels, and may continue to detect high CO levels, but may then detect alow temperature below its low temperature safety threshold. In suchcases, it may reactivate the heat source, under the assumption that nopersons are being affected by the CO levels (e.g., there is nobody home)but if not heated to at least the low temperature safety threshold,pipes would freeze and burst. In such cases, and in all cases where highlevels of CO are detected while no persons appear to be present in thehome, the smart thermostat and/or other smart devices of the smart-homeenvironment may provide audible and/or flashing light warning messagesas soon as motion is detected at any of the smart devices.

FIG. 20D is a flowchart of a method 3000 of determining CO baselineconditions and setting alarm thresholds in a smart-home environment. Inembodiments, method 3000 is typically used to set an alarm threshold forpre-hazardous CO conditions at a particular location in a particularsmart-home environment, so that pre-hazardous condition alarms representabnormal CO increases for that particular location and environment.However, the threshold is generally set much lower than a dangerous COlevel, so that causes can be determined and/or a CO increase can bebrought to a user's attention well before safety becomes an issue. It isalso possible to set multiple thresholds for pre-hazardous CO alerts, asdiscussed further below in connection with FIG. 20E.

Method 3000 begins with step 3005 measuring an ambient CO level. Anexample of step 3005 is hazard detector 104 measuring CO level at itslocation. Hazard detector 104 typically continues to measure CO levelsuch that method 3000 shows step 3005 continuously repeating, inaddition to the further steps of the method. In an optional step 3010,the CO measurement, the identity or location of the hazard detector 104that measured the CO, and time of day that the CO was measured, aretransmitted to an analyzing system. Step 3010 need not be performed whenhazard detector 104 is the analyzing system. Examples of step 3010 arehazard detector 3010 transmitting CO data to a smart thermostat 102,computer 166 or cloud-computing system 164 (for example, by way ofwireless router 160, FIG. 1). Step 3010 optionally also includestransmitting a time of day of the CO measurement transmitted; the timeof day information is not required in all embodiments and/or may beinferred by the analyzing system (e.g., a time of day that the measureddata is received by the analyzing system may be considered as the timeof day of the measurement). In another optional step 3015, method 3000receives other smart-home environment data at the analyzing system. Theother smart-home environment data could be anything measurable by smartdevices, such as temperature, light, sound, smoke, motion, operationalstates, alarm states and the like. Any such data that is available inthe smart-home environment may be possible to correlate directly orindirectly to CO measurements.

Step 3020 analyzes the CO measurements to determine a threshold for apre-hazardous condition. Step 3020 is typically performed after asignificant number of measurements exist, such as 30 or moremeasurements in a population. In one embodiment, the populationrepresents all operating conditions, e.g., the CO measurements are notscreened or segregated by time of day or in connection with othermeasurable events or circumstances. In other embodiments, the COmeasurements are screened or analyzed as subsets according to time ofday or other circumstances (see FIG. 20E). The analysis can be performedin a variety of ways, for example, the analyzing system may perform amean and standard deviation analysis on the population of COmeasurements, and assign a pre-hazardous condition thresholdcorresponding to mean plus two, three, four or more standard deviations.Alternatively, for a large population of CO measurements (e.g., morethan 100 or 1000 measurements), the analyzing system may assign thethreshold slightly above the highest CO measurement of the population.Those skilled in the statistical arts will appreciate that many forms ofanalyzing CO measurement populations to come up with alarm limits thatrepresent CO excursions that are statistically significant, arepossible.

An optional step 3025 compares the threshold to one or more other humanCO exposure standards for validation. If the determined thresholdexceeds and/or is within a predetermined tolerance of such standards,the calculated threshold may be optionally brought to a person'sattention in step 3030. Step 3030 may bring the high determinedthreshold to a person's attention by highlighting it in a table of alertconditions, through an app alert, by generating a log message that isperiodically reviewed, or by sending an email or text message to theperson. The predetermined tolerance may be, for example, if thethreshold is greater than 75% of an applicable UL standard, or one ofthe location-specific thresholds noted in column 2520, FIG. 17. Thetolerance may also be considered in context of the type of exposurestandard; for example thresholds that are near to long term exposurestandards may be considered less important than threshold that are nearto short term danger levels. The person to whose attention the thresholdis brought may be a user or resident of the smart-home environment, orsomeone associated with a cloud-computing system that calculates thethreshold. There are several reasons for bringing high calculatedthresholds to someone's attention. A high threshold may signify that aparticular smart-home environment has a chronic or poorly controlled COsource that needs to be understood; it may signify that the analysisthat resulted in the high threshold was flawed and should be reviewedand corrected; and if implemented, an alerts based on a high thresholdis possibly likely to be followed imminently by a hazardous conditionalert, because the pre-hazardous condition alert is only slightly lowerthan the hazardous condition threshold. After review, the person whoreviews the determined threshold may decide in step 3035 to implementthe threshold anyway, or take some other action, such as order furthermeasurements or investigate the smart-home environment for CO sources.

If the decision in step 3025 is that the threshold is not high enough tohuman exposure standards, or the result of a human decision in step 3035is to implement the threshold anyway, the threshold determined in step3020 may be capped or adjusted in step 3037 as compared to theapplicable hazardous condition threshold (e.g., the pre-hazardous alertmay be set equal to the hazard threshold, or automatically reduced by afactor such as 10% or 20% relative to the hazard threshold). Thethreshold is then transmitted back to the hazard detector 104 that tookthe original measurements in a step 3040, in cases where the analyzingsystem was not the hazard detector itself. In step 3045, the thresholdis implemented as a pre-hazardous condition alert threshold in thehazard detector 104.

Method 3000, FIG. 20D, calculates and implements a single CO threshold.When a single threshold is deemed adequate for all situations, times ofday and the like, method 3000 is adequate. However, in embodiments,multiple CO thresholds are desirable so that individual ones of thethresholds can be raised or lowered in accordance with uniquecircumstances. Multiple thresholds therefore allow low thresholds ofknown, well controlled locations, times or other circumstances, andhigher thresholds for locations, times or other circumstances that arecharacterized by predictable CO excursions that would trigger nuisancealarms at the lower threshold.

FIG. 20E is a flowchart of a method 3050 of setting multiplepre-hazardous CO alarm thresholds for a smart-home environment. Method3050 is substitutable for step 3020 of method 3000, FIG. 20D, in that itis performed by an analyzing system of the smart-home environment (e.g.,one of the smart devices thereof, an app of an associated computingdevice such as computer 166, or cloud-computing system 164). Method 3050will typically also be followed by steps 3025 and beyond of method 3000,such as validating the multiple CO thresholds against human CO standardsand transmitting the thresholds back to a detector that will implementthem.

Method 3050 begins with a step 3060 of establishing a CO criterion todistinguish two (or more) subsets of CO data. The CO criterion should besomething that is available to the smart-home network on a continuousbasis, such as time of day or a metric that can be evaluated with datagenerated by the smart-home network, such as a setting, a status code orcorrelation in time to a smart-home characteristic measured by one ormore smart devices. For example, a simple CO criterion might be definedto distinguish CO measurements during a time block of 7:00 a.m. to 9:00a.m. on weekdays, vs. all other times. Alternatively, more complex COcriteria may be established, such as any time within one-half hour of acertain door sensor (e.g., garage door or door from garage to house)being activated, any time within one hour of any motion being detectedin a kitchen, or whether occupants are determined to be “at home” or“away” as described below. The CO criterion may be supplied by a user oradministrator of the system, or it may be generated by an analyzingsystem of the smart-home network through correlation trials.

Once the CO criterion is established, method 3050 assigns existing COmeasurement data (obtained by the analyzing system in steps 3005-3015,FIG. 20D) into subsets according to the CO criterion, in step 3070. Instep 3080, each subset is analyzed to determine an appropriate thresholdfor a pre-hazardous alert. Evaluation of these subsets proceeds asdescribed in step 3020, FIG. 20D, except that the evaluation isperformed for each subset of the CO measurement data, producing acorresponding threshold for each of the subsets. When the multiplethresholds according to the subsets are communicated, the applicable COcriterion for each threshold is also communicated, in step 3090.

Once the multiple pre-hazardous CO thresholds are implemented, a hazarddetector 104 may constantly evaluate and utilize the CO criterion todetermine which of the thresholds it should use to compare against acurrent CO level. Alternatively, the hazard detector 104 may notnecessarily evaluate the CO criterion unless current CO exceeds a firstthreshold, whereupon it will evaluate the CO criterion to determinewhether current conditions call for a different threshold to be used.

Exemplary Computer Environments, Including Special Purpose Computers

Referring next to FIG. 21, an exemplary environment with whichembodiments may be implemented is shown with a computer system 3500 thatcan be used by a user 3504 to remotely control, for example, one or moreof the sensor-equipped smart-home devices according to one or more ofthe embodiments. Computer system 3500 can alternatively be used forcarrying out one or more of the server-based processing paradigmsdescribed hereinabove or as a processing device in a larger distributedvirtualized computing scheme for carrying out the described processingparadigms, or for any of a variety of other purposes consistent with thepresent teachings. Computer system 3500 can include a computer 3502,keyboard 3522, a network router 3512, a printer 3508, and a monitor3506. Monitor 3506, processor 3502 and keyboard 3522 may be consideredpart of a computer system 3526, which can be a laptop computer, desktopcomputer, handheld computer, mainframe computer, etc. Monitor 3506 canbe a CRT, flat screen, etc.

A user 3504 can input commands into computer 3502 using various inputdevices, such as a mouse, keyboard 3522, a track ball, a touch screen,etc. If computer system 3500 includes a mainframe, user 3504 may accessthe computer 3502 using, for example, a terminal or terminal interface.Additionally, computer system 3526 may be connected to a printer 3508and a server 3510 using a network router 3512, which may connect to theInternet 3518 or a WAN.

Server 3510 may, for example, store additional software programs anddata. In one embodiment, software implementing the systems and methodsdescribed herein can be stored on a storage medium in server 3510. Thus,the software can be run from the storage medium in server 3510. Inanother embodiment, software implementing the systems and methodsdescribed herein can be stored on a storage medium in computer 3502.Thus, the software can be run from the storage medium in computer 3502.Therefore, in this embodiment, the software can be used whether or notcomputer 3502 is connected to network router 3512. Printer 3508 may beconnected directly to computer 3502, in which case, computer system 3526can print whether or not it is connected to network router 3512.

FIG. 22 schematically illustrates an embodiment in the form of aspecial-purpose computer system 3600. For example, one or moreintelligent components, one or more processing engines 206 and/orcomponents thereof may reside in special-purpose computer system 3600.The above methods may be implemented by computer-program products thatdirect a computer system to perform the actions of the above-describedmethods and components. Each such computer-program product may comprisesets of instructions (codes) embodied on a non-transitory,computer-readable medium that directs the processor of a computer systemto perform corresponding actions. The instructions may be configured torun in sequential order, or in parallel (such as under differentprocessing threads), or in a combination thereof. After loading thecomputer-program products on a general purpose computer system 3626, itis transformed into the special-purpose computer system 3600.

Special-purpose computer system 3600 comprises one or more of a computer3602, a monitor 3606 coupled to computer 3602, one or more additionaluser output devices 3630 (optional) coupled to computer 3602, one ormore user input devices 3640 (e.g., keyboard, mouse, track ball, touchscreen) coupled to computer 3602, an optional communications interface3650 coupled to computer 3602, and/or a computer-program product 3605stored in a tangible computer-readable memory in computer 3602.Computer-program product 3605 directs system 3600 to perform theabove-described methods. Computer 3602 may include one or moreprocessors 3660 that communicate with a number of peripheral devices viaa bus subsystem 3690. These peripheral devices may include user outputdevice(s) 3630, user input device(s) 3640, communications interface3650, and a storage subsystem, such as random access memory (RAM) 3670and non-volatile storage 3680 (e.g., a disk drive, an optical drive,and/or non-transitory, solid state memory such as Flash, one-timeprogrammable, or read-only memory), which are forms of tangiblecomputer-readable memory.

Computer-program product 3605 may be stored in non-volatile storage 3680or another computer-readable medium accessible to computer 3602 andloaded into memory 3670. Each processor 3660 may comprise amicroprocessor, such as a microprocessor from Intel® or Advanced MicroDevices, Inc.®, or the like. To support computer-program product 3605,the computer 3602 runs an operating system that handles thecommunications of product 3605 with the above-noted components, as wellas the communications between the above-noted components in support ofthe computer-program product 3605. Exemplary operating systems includeWindows® or the like from Microsoft Corporation, Solaris® from SunMicrosystems, LINUX, UNIX, and the like.

User input devices 3640 include all possible types of devices andmechanisms to input information to computer system 3602. These mayinclude a keyboard, a keypad, a mouse, a scanner, a digital drawing pad,a touch screen incorporated into a display, audio input devices such asvoice recognition systems, microphones, and other types of inputdevices. In various embodiments, user input devices 3640 are typicallyembodied as a computer mouse, a trackball, a track pad, a joystick,wireless remote, a drawing tablet, a voice command system. User inputdevices 3640 typically allow a user to select objects, icons, text andthe like that appear on the monitor 3606 via a command such as a clickof a button or the like. User output devices 3630 include all possibletypes of devices and mechanisms to output information from computer3602. These may include a display (e.g., monitor 3606), printers, and/ornon-visual displays such as audio output devices, etc.

Communications interface 3650 provides an interface to othercommunication networks and devices and may serve as an interface toreceive data from and transmit data to other systems, WANs and/or theInternet 3518. Embodiments of communications interface 3650 typicallyinclude an Ethernet card, a modem (telephone, satellite, cable, ISDN), a(asynchronous) digital subscriber line (DSL) unit, a FireWire®interface, a USB® interface, a wireless network adapter, and the like.For example, communications interface 3650 may be coupled to a computernetwork, to a FireWire® bus, or the like. In other embodiments,communications interface 3650 may be physically integrated on themotherboard of computer 1602, and/or may be a software program, or thelike.

RAM 3670 and non-volatile storage 3680 are examples of tangiblecomputer-readable media configured to store data such ascomputer-program product embodiments of the present invention, includingexecutable computer code, human-readable code, or the like. Other typesof tangible and/or non-transitory computer-readable media include floppydisks, removable hard disks, optical storage media such as CD-ROMs,DVDs, bar codes, semiconductor memories such as flash memories,read-only-memories (ROMs), battery-backed volatile memories, networkedstorage devices, and the like. RAM 3670 and non-volatile storage 3680may be configured to store the basic programming and data constructsthat provide the functionality of various embodiments of the presentinvention, as described above.

Software instruction sets that provide the functionality of the presentinvention may be stored in RAM 3670 and non-volatile storage 3680. Theseinstruction sets or code may be executed by the processor(s) 3660. RAM3670 and non-volatile storage 3680 may also provide a repository tostore data and data structures used in accordance with the presentinvention. RAM 3670 and non-volatile storage 3680 may include a numberof memories including a main random access memory (RAM) to storeinstructions and data during program execution and a read-only memory(ROM) in which fixed instructions are stored. RAM 3670 and non-volatilestorage 3680 may include a file storage subsystem providing persistent(non-volatile) storage of program and/or data files. RAM 3670 andnon-volatile storage 3680 may also include removable storage systems,such as removable flash memory.

Bus subsystem 3690 provides a mechanism to allow the various componentsand subsystems of computer 3602 to communicate with each other asintended. Although bus subsystem 3690 is shown schematically as a singlebus, alternative embodiments of the bus subsystem may utilize multiplebusses or communication paths within the computer 3602.

For a firmware and/or software implementation, the methodologies may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. Any machine-readable mediumtangibly embodying instructions may be used in implementing themethodologies described herein. For example, software codes may bestored in a memory. Memory may be implemented within the processor orexternal to the processor. As used herein the term “memory” refers toany type of long term, short term, volatile, nonvolatile, transitory,non-transitory, and/or other storage medium and is not to be limited toany particular type, number or configuration of memories, or type ofmedia upon which memory is stored.

Moreover, as disclosed herein, the term “storage medium” may representone or more memories for storing data, including read only memory (ROM),random access memory (RAM), magnetic RAM, core memory, magnetic diskstorage mediums, optical storage mediums, flash memory devices and/orother machine readable mediums for storing information. The term“machine-readable medium” includes, but is not limited to portable orfixed storage devices, optical storage devices, wireless channels,and/or various other storage mediums capable of storing that contain orcarry instruction(s) and/or data.

A hazard detector according to an embodiment of the present inventionmay include a smoke, carbon monoxide (CO) and heat alarm for residentialapplications, similar to other hazard detectors discussion herein (e.g.,smart hazard detectors 104 and 400, as shown in FIGS. 1 and 4,respectively). This hazard detector may utilize batteries (e.g., sixlithium AA batteries or the batteries of battery pack 450, as shown inFIG. 4A). Alternatively, a hazard detector may be hard-wired, e.g.,hard-wired via a 120V home power line, and/or may include a backupbattery, e.g., any of the batteries discussed herein.

A hazard detector may advantageously integrate seven sensors: aphotoelectric smoke sensor, a heat sensor, a carbon monoxide sensor thatmay last approximately 7 years, an ultrasonic sensor (e.g., first andsecond ultrasonic sensors 972 and 974, as shown in FIG. 5A), anoccupancy sensor (e.g., a PIR sensor), an ambient light sensor and ahumidity sensor. The use of these different sensors, in addition toadvanced algorithms (e.g., as referenced in relation to FIGS. 1-5B) mayallow the hazard detector to use multi-criteria detection to providenumerous features and functionality in addition to the features requiredby applicable regulatory agencies for basic alarm/detectionfunctionality. Data from the temperature, humidity, occupancy andambient light sensors may also be shared with other network connecteddevices (e.g., any of the devices shown in FIG. 1).

A number of different features related to alarms and hazard detectorfunctionality verification of a hazard detector are now described.

For the purpose of detecting smoke, carbon monoxide and heat andgenerating corresponding emergency alarms, the hazard detector mayinclude a photoelectric smoke sensor, a carbon monoxide sensor that mayfollow the time response required by Underwriters' Laboratories (“UL”),and a heat sensor whose sensitivity may be “135”. The hazard detectormay provide voice alarms with hazard location and call-to-actioninformation. For example, to alert users that a danger or hazard hasbeen sensed by the hazard detector, the hazard detector may generatevoice alarms that include speech to announced what type of danger hasbeen sensed (e.g., Smoke, CO, and/or Heat), where the danged has beensensed (e.g., in the living room, the bedroom, or a specific bedroom),and how the user should respond to the sensed danger (e.g., get out of aspecific room or a residence). The voice alarms may also include thesound patterns required by applicable hazard detector regulations. Forexample, if smoke is sensed in the hallway, the hazard detector maygenerate the following voice alarm: “Honk, honk. EMERGENCY! There issmoke in the Hallway. Get out now.” “Honk,” as used herein, may refer toa shrill, loud, piercing audio sound or any other sound traditionallyassociated with a “honk” sound. As another example, if carbon monoxideis sensed in the hallway, the hazard detector may generate the followingvoice alarm: “Honk, honk. EMERGENCY! There is carbon monoxide in thehallway. Move to fresh air immediately.” During an alarm, lights (e.g.,LED lights) of the hazard detector may flash red or another color. Inorder to provide the hazard detector's location during an alarm, thehazard detector may be associated with a room of a residence or otherbuilding during the hazard detector setup process (e.g., using method1300, FIG. 6).

The hazard detector may be installed in multiple locations in a singlehome or other building. Some or all of these hazard detectors can beinterconnected wirelessly. As such, when a first hazard detector locatedin a hallway senses smoke and generates an alarm, other hazard detectorsinterconnected with the first hazard detector may wirelessly receive acommand to generate the same voice alarms. The wireless interconnectionbetween hazard detectors may occur over 6LoWPAN or other low-powercommunication protocols, and may not require a Wi-Fi connection or useof a mobile device application or app (e.g., application 1414, as shownin FIGS. 7-10) to establish the wireless interconnection. Even whenmultiple hazard detectors in a home generate the same voice alarm, auser may be able to quickly identify the first hazard detector—thehazard detector that first sensed the hazard and generated acorresponding alarm—because the name of the first hazard detector'slocation (e.g., the bedroom or the kitchen) may be included in the voicealarm.

Users may temporarily silence or “hush” certain alarms of the hazarddetector by waving at the hazard detector, as described below. However,the hazard detector alarm may only be temporarily silenced and only ifthe sensed hazard levels are within a range in which applicableregulatory agencies allow hazard detector alarms to be silenced.“Waving,” as used above, refers to a user's movement of his or her handand/or other body part back and forth and/or up and down. The hazarddetector may determine when waving is occurring using methods describedin the following related U.S. patent application: U.S. Prov. Ser. No.61/847,960 filed Jul. 18, 2013 (Ref. No. NES0307-PROV). Waving may bemore convenient for users than climbing on a ladder or using a broom toreach the hazard detector and manually depress a silencing buttonthereon. As an example, during an alarm and/or a Heads Up pre-alarm (asdescribed below), the hazard detector may determine that someone iswithin the sensing range of the occupancy sensor of the initiatinghazard detector. Thereafter, when waving is detected by that hazarddetector, it may generate a speech stating that the alarm will besilenced or hushed temporarily. The hazard detector may be configuredsuch that only adult-sized users can silence or hush a voice alarm; thisfeature may be operable to exclude children and pets from being able tosilence an alarm. For example, sensitivity of motion sensors of thehazard detector may be set such that only adult-sized users (includingadult users in a wheelchair) can be sensed for the purpose of detectingwaving to silence or hush an alarm. The hazard detector may alsoinclude, for example, a hush/test button that can be depressed to hushor silence an alarm.

In addition to the voice alarms described above, the hazard detector mayprovide additional early notifications, referred to herein aspre-alarming or heads-up notifications, of an evolving situation, orprogressively more dangerous hazard levels. That is, heads-upnotifications provide a warning to the user that a pre-hazardouscondition has been detected in which there are elevated readingscorresponding to the type of hazard being detected, but those readingsdo not yet rise to levels corresponding to an actual alarm condition.Generally, a pre-alarm or heads-up condition is one that merits moreimmediacy of concern than those underlying typical,persistent-yet-pleasant modulated glow levels of communication that areprovided by smart thermostats and smart hazard detectors herein. Apre-alarm or heads-up condition may be accompanied by an immediateaudible message. However, heads-up notifications may provide afriendlier voice alarm—in terms of content and tone—to alert users whensmoke and/or CO are rising toward, but have not reached, hazardouslevels. For example, the friendlier voice may be more calm, use lessurgent language and may not be accompanied by sound patterns typicallyassociated with emergency situations (e.g., a doorbell chime instead ofa siren). As such, heads-up notifications may avoid alarming users to adegree that is not commensurate with the urgency of a given detectedhazard level, while still alerting the user to a situation that mayrequire attention. For example, if the hazard detector senses low levelsof smoke, the hazard detector may generate the following speech “Headsup. There is smoke in the kitchen. The horn may sound.” During aheads-up voice alarm, lights (e.g., LED lights) of the hazard detectormay flash yellow. Heads-up notifications may be disabled via a mobileapplication (e.g., application 1414, as shown in FIGS. 7-10), by thehazard detector's online management account (e.g., the online managementaccount discussed in relation to FIG. 6), and/or at the hazarddetector's user interface.

Gating Gesture Hush

Referring now to FIGS. 23 and 24, interaction of a user 608 with a smarthazard detector 104 by providing exemplary “silence gestures” todeactivate or “hush” an alarm will be described. In the event hazarddetector 104 is sounding an alarm, a user can walk to a positionproximate the hazard detector 104 and provide a silence gesture to causethe hazard detector to stop alarming. The signal or input that isreceived by smart hazard detector 104 or other smart devices herein maybe referred to as “gesture input.” As shown in FIG. 23 at step 604, anoccupant is standing in room 612 while an alarm in smoke or hazarddetector 104 is active and making a “BEEP” sound. A light 610, such asan LED, is provided on an outer portion of the smart hazard detector104, such that the occupant 608 can see the light 610 when it is turnedon. The operation of the light 610 will be described with reference toFIG. 24. Suffice to say for FIG. 23, the light is turned off in steps604 through 624. As shown at step 616, the occupant 608 has walked to aposition closer to the smart hazard detector 104, which is mounted outof reach on the ceiling of the room. As shown at step 620, the occupant608 walked to a position even closer to the smart hazard detector 104,such that the occupant 608 is almost directly under the smart hazarddetector 104. As shown at arrow 628 of step 624, the occupant 608, whilestanding almost directly under the smart hazard detector 104, isbeginning to extend an arm upward, toward the smart hazard detector 104.

Referring now to step 630 of FIG. 24, the arm of the occupant 608 isextended upward, toward the smart hazard detector 104, while theoccupant is standing almost directly under the smart hazard detector104. After an alarm sounds and the pulse rate increases, the ultrasonicsensor the smart hazard detector 104 “looks” for a trigger to the“silence gesture” period, which is the amount of time the “silencegesture” must be maintained to deactivate the alarm. According to someembodiments, the trigger is a distance change from a baseline, and todeactivate the alarm the distance change must be maintained for theentire “silence gesture” period (e.g., three seconds). For example, ifthe baseline is a distance between the sensor and the floor of the room,then the sensor is looking for an object to come in between it and thefloor, thereby changing the distance measured by the sensor. In someembodiments, the distance change must be significant enough to ensurethat someone is close and likely intends to silence the alarm. Forexample, if the distance to the floor is ten feet, then the requisitedistance change could be eight feet or eighty percent of the originaldistance. As such, the object would be required to be within two feet ofthe sensor to trigger the “silence gesture” period, and to deactivatethe alarm, the object must remain there for the duration of the period.The requisite distance change can be configured based on the height ofthe ceiling and based on the height of the occupants, among otherthings.

Referring still to step 630, the light 610 is turned on when theoccupant 608 successfully triggers the “silence gesture” period, therebysignaling to the occupant 608 to remain in the position for therequisite period, such as three seconds. Here, the hand of the occupant608 triggered the “silence gesture” period. A tolerance is built in suchthat if the occupant 608 slightly moves and loses but quickly regainsthe signal, the “silence gesture” period will continue without having tostart over. As shown in step 634, the occupant kept the hand in withinthe requisite distance of the sensor for the duration of the “silencegesture” period and, thus the alarm has been deactivated, the “BEEP” hasstopped, and the light 610 has turned off. As shown at steps 638 and642, the occupant 608 can walk away from the smart hazard detector 104and resume normal activity.

It should be appreciated that, in the event the smart hazard detector104 is of a design that receives reliable power from the wiring of thehome (rather than being battery powered), a CCD chip could be used todetect gesture input such as the “silence gesture”. However, such anarrangement may be less suitable than ultrasonic sensors (e.g.,ultrasonic sensors 972 and 974, FIG. 5A) for battery-powered hazarddetectors 104 because the CCD chips and associated processing canconsume a relatively large amount of power and may quickly drain thebattery. Other possible alternatives to ultrasonic sensors 972 and 974include passive IR sensors, thermopile (e.g., thermo-cameras),laser-distance measuring, laser and camera combinations wherein, forexample, a camera looks for a laser dot instead of time of arrival(Doppler shift), and full on camera and image processing systems.

According to some embodiments, to enhance the reliability andeffectiveness of gesture input, the ultrasonic sensor 972 and/or 974could work in concert with a PIR sensor to make the sensing even better.For example, when an occupant attempts to silence by placing a hand in afield of view of the PIR sensor, the PIR sensor may sense this, andthereby trigger the “silence gesture” or “hushed” period. The ultrasonicsensor 972 and/or 974 could also work in concert with the thermopile(e.g., thermo-camera), where both distance change and heat are used todetect the “silence gesture.” For example, the thermo-camera detectswhen human hand is nearby and triggers the “silence gesture” period.Further, ultrasonic sensors 972 and/or 974 may work in concert with anambient light sensor. For example, when a user places a hand in s fieldof view of an ambient light sensor and blocks light thereon, then theambient light sensor knows that the occupant is nearby and thus triggersthe “silence gesture” period.

It should be appreciated that, according to embodiments, similar gestureinput can be recognized by other smart devices in the home, such as thesmart thermostat, the smart wall switches, etc. For example, there canbe gestures for increasing or decreasing temperature controls, forturning on and off lights, HVAC, etc.

It should be appreciated that, according to embodiments, an occupancysensor “gates” the silence gesture by only permitting a silence gestureto occur if the room is occupied. In other words, hazard detector 104may not “listen” for a silence gesture unless it determines that theroom is occupied. By disabling its silence gesture feature when the roomis unoccupied, hazard detector ensures that the silence gesture featuredoes not malfunction during an alarm event and improperly deactivate analarm.

Smart Thermostat

Turning now to FIGS. 25A-B, illustrations of a smart thermostat 102 areprovided, according to some embodiments. Unlike many prior artthermostats, smart thermostat 102 may provide a sleek, simple,uncluttered and elegant design that does not detract from homedecoration, and indeed can serve as a visually pleasing centerpiece forthe immediate location in which it is installed. Moreover, userinteraction with smart thermostat 102 is facilitated and greatlyenhanced over known conventional thermostats by the design of smartthermostat 102. The smart thermostat 102 includes control circuitry andis electrically connected to an HVAC system, such as is shown with unit103 in FIG. 1. Smart thermostat 102 is wall mounted, is circular inshape, and has an outer rotatable ring 3112 for receiving user input.Smart thermostat 102 is circular in shape in that it appears as agenerally disk-like circular object when mounted on the wall.

The outer rotatable ring 3112 allows the user to make adjustments, suchas selecting a new target temperature. For example, by rotating theouter ring 3112 clockwise, the target temperature can be increased, andby rotating the outer ring 3112 counter-clockwise, the targettemperature can be decreased. The smart thermostat 102 may be configuredto receive a plurality of types of inputs by virtue of the rotatablering 3112, such as a scrolling input and a selection input. For example,a rotation of the ring may allow a user to scroll through an array ofselection options, and inwards pressure exerted on the ring (inwardclick) may allow a user to select one of the options (e.g.,corresponding to a particular scroll position).

The front face of the smart thermostat 102 comprises a clear cover 3114that according to some embodiments is polycarbonate, and a metallicportion 3124 that may advantageously have a number of slots formedtherein, as shown. Metallic portion 3124 as incorporated in smartthermostat 102 does not detract from home or commercial decor, andindeed can serve as a visually pleasing centerpiece for the immediatelocation in which it is located.

Although being formed from a single lens-like piece of material such aspolycarbonate, the cover 3114 has two different regions or portionsincluding an outer portion 3114 o and a central portion 3114 i.According to some embodiments, the cover 3114 is painted or smokedaround the outer portion 3114 o, but leaves the central portion 3114 ivisibly clear so as to facilitate viewing of an electronic display 3116disposed thereunderneath. According to some embodiments, central display3116 is a backlit color liquid crystal display (LCD). An example ofinformation displayed on the electronic display 3116 is illustrated inFIG. 25A, and includes central numerals 3120 that are representative ofa current setpoint temperature.

Particular presentations displayed on the electronic display 3116 maydepend on detected user input. For example, one of a plurality ofvariables (e.g., current setpoint temperature versus learning status) orvariable values (e.g., “65” versus “75”) may be displayed. The one beingdisplayed may depend on a user's rotation of the outer rotatable ring3112. Thus, for example, when the device is configured to display acurrent setpoint temperature, the value being displayed may graduallyincrease as the user rotates the ring in a clockwise direction. The signof the change in the displayed temperature may depend on whether theuser is rotating the ring in a clockwise or counterclockwise direction.The speed at which the displayed temperature is changing may depend(e.g., in a linear manner) on the speed at which the user is rotatingthe ring.

The metallic portion 3124 is designed to conceal sensors from viewpromoting a visually pleasing quality of the thermostat yet permittingthem to receive their respective signals. Openings in the metallicportion 3124 along the forward-facing surface of the housing allowsignals to pass through that would otherwise not pass through the cover3114. For example, glass, polycarbonate or other similar materials usedfor cover 3114 are capable of transmitting visible light but are highlyattenuating to infrared energy having longer wavelengths in the range of10 microns, which is the radiation band of operation for many passiveinfrared (PIR) occupancy sensors. Notably, included in the smartthermostat 102, according to some preferred implementations, is anambient light sensor (not shown) and an active proximity sensor (notshown) positioned near the top of the thermostat just behind the cover3114. Unlike PIR sensors, the ambient light sensor and active proximitysensor are configured to detect electromagnetic energy in the visibleand shorter-infrared spectrum bands having wavelengths less than 1micron, for which the glass or polycarbonate materials of the cover 3114are not highly attenuating. In some implementations, the metallicportion 3124 includes openings in accordance with one or moreimplementations that allow the longer-wavelength infrared radiation topass through the openings towards a passive infrared (PIR) motion sensor3130 as illustrated. Because the metallic portion 3124 is mounted overthe radiation receiving surface of PIR motion sensor 3130, PIR motionsensor 3130 continues to receive the longer wavelength infraredradiation through the openings and detect occupancy in an enclosure.

Additional implementations of the metallic portion 3124 also facilitateadditional sensors to detect other environmental conditions. Themetallic portion may at least partly conceal and/or protect one or moresuch sensors. In some implementations, the metallic portion 3124 helps atemperature sensor situated inside of the thermostat's housing measurethe ambient temperature of air. Openings in the metallic portion 3124promote air flow towards a temperature sensor located below the metallicportion 3124 thus conveying outside temperatures to the interior of thehousing. In further implementations, the metallic portion 3124 may bethermally coupled to a temperature sensor promoting a transfer of heatfrom outside the housing.

An LED indicator 3180 can be used for communicating one or more statuscodes or error codes by virtue of red color, green color, variouscombinations of red and green, various different blinking rates, and soforth, which can be useful for troubleshooting purposes.

Motion sensing as well as other techniques can be used in the detectionand/or prediction of occupancy, as it is described further in thecommonly assigned U.S. Ser. No. 12/881,430, supra. According to someembodiments, occupancy information is used in generating an effectiveand efficient scheduled program. Advantageously, an active proximitysensor 3170A is provided to detect an approaching user by infrared lightreflection, and an ambient light sensor 3170B is provided to sensevisible light. The proximity sensor 3170A can be used to detectproximity in the range of about one meter so that the smart thermostat102 can initiate “waking up” when the user is approaching the thermostatand prior to the user touching the thermostat. Such use of proximitysensing is useful for enhancing the user experience by being “ready” forinteraction as soon as, or very soon after the user is ready to interactwith the thermostat. Further, the wake-up-on-proximity functionalityalso allows for energy savings within the thermostat by “sleeping” whenno user interaction is taking place our about to take place. The ambientlight sensor 3170B can be used for a variety of intelligence-gatheringpurposes, such as for facilitating confirmation of occupancy when sharprising or falling edges are detected (because it is likely that thereare occupants who are turning the lights on and off), and such as fordetecting long term (e.g., 24-hour) patterns of ambient light intensityfor confirming and/or automatically establishing the time of day.

According to some embodiments, for the combined purposes of inspiringuser confidence and further promoting visual and functional elegance,the smart thermostat 102 is controlled by only two types of user input,the first being a rotation of the outer ring 3112 as shown in FIG. 10A(referenced hereafter as a “rotate ring” or “ring rotation” input), andthe second being an inward push on an outer cap 3108 (see FIG. 25B)relative to an outer shell 3109 until an audible and/or tactile “click”occurs (referenced hereafter as an “inward click” or simply “click”input). For the embodiment of FIGS. 25A and 25B, the outer cap 3108 isan assembly that includes all of the outer ring 3112, cover 3114,electronic display 3116, and metallic portion 3124. When pressedinwardly by the user, the outer cap 3108 travels inwardly by a smallamount, such as 0.5 mm, against an interior metallic dome switch (notshown), and then springably travels back outwardly by that same amountwhen the inward pressure is released, providing a satisfying tactile“click” sensation to the user's hand, along with a corresponding gentleaudible clicking sound. Thus, for the embodiment of FIGS. 25A and 25B,an inward click can be achieved by direct pressing on the outer ring3112 itself, or by indirect pressing of the outer ring by virtue ofproviding inward pressure on the cover 3114, metallic portion 3124, orby various combinations thereof. For other embodiments, the smartthermostat 102 can be mechanically configured such that only the outerring 3112 travels inwardly for the inward click input, while the cover3114 and metallic portion 3124 remain motionless. It is to beappreciated that a variety of different selections and combinations ofthe particular mechanical elements that will travel inwardly to achievethe “inward click” input are within the scope of the present teachings,whether it be the outer ring 3112 itself, some part of the cover 3114,or some combination thereof. However, it has been found particularlyadvantageous to provide the user with an ability to quickly go back andforth between registering “ring rotations” and “inward clicks” with asingle hand and with minimal amount of time and effort involved, and sothe ability to provide an inward click directly by pressing the outerring 3112 has been found particularly advantageous, since the user'sfingers do not need to be lifted out of contact with the device, or slidalong its surface, in order to go between ring rotations and inwardclicks. Moreover, by virtue of the strategic placement of the electronicdisplay 3116 centrally inside the rotatable ring 3112, a furtheradvantage is provided in that the user can naturally focus theirattention on the electronic display throughout the input process, rightin the middle of where their hand is performing its functions. Thecombination of intuitive outer ring rotation, especially as applied to(but not limited to) the changing of a thermostat's setpointtemperature, conveniently folded together with the satisfying physicalsensation of inward clicking, together with accommodating natural focuson the electronic display in the central midst of their fingers'activity, adds significantly to an intuitive, seamless, and downrightfun user experience. Further descriptions of advantageous mechanicaluser-interfaces and related designs, which are employed according tosome embodiments, can be found in U.S. Ser. No. 13/033,573, supra, U.S.Ser. No. 29/386,021, supra, and U.S. Ser. No. 13/199,108.

According to some embodiments, the smart thermostat 102 includes aprocessing system 3160, memory 3162, display driver 3164 and a wirelesscommunications system 3166. The processing system 3160 may be disposedwithin a housing of smart thermostat 102, coupled to one or moretemperature sensors of smart thermostat 102 and/or coupled to rotatablering 3112. The processing system 3160 may be configured to dynamicallyidentify user input via rotatable ring 3112, dynamically identifying avariable value (e.g., a setpoint temperature value), and/or dynamicallyidentify an HVAC-control-related property. The processing system 3160may be configured and programmed to provide an interactive thermostatmenuing system on display area 3116 responsive to an inward pressing ofrotatable ring 3112 and/or to provide user navigation within theinteractive thermostat menuing system based on rotation of rotatablering 3112 and inward pressing of rotatable ring 3112. The processingsystem 3160 may be adapted to cause the display driver 3164 and displayarea 3116 to display information to the user and/or to receive userinput via the rotatable ring 3112. Memory 3162 may include volatile(e.g., RAM) and/or nonvolatile memory (e.g., ROM and/or Flash memory)for storing information such as current and previous user-indicatedsettings, what type of heating system is associated with an HVAC systembeing controlled, and the like.

For example, an active variable (e.g., variable-value selection,setpoint selection, zip-code selection) may be determined based on adefault state, smart logic or previously received user input. Arelationship between the variable and user input may be identified. Therelationship may be, e.g., linear or non-linear, continuous or discrete,and/or saturating or non-saturating. Such relationships may bepre-defined and stored within the thermostat. User input may bedetected. Analysis of the user input may include, e.g., identifying: atype of user input (tapping versus rotation), a degree of input (e.g., adegree of rotation); a final input position (e.g., a final angularposition of the rotatable ring); an input location (e.g., a position ofa tapping); and/or a speed of input (e.g., a speed of rotation). Usingthe relationship, the processing system 3160 may then determine adisplay indicator, such as a digital numerical value representative ofan identified value of a variable (e.g., a setpoint temperature). Thedisplay indicator may be displayed on display area 3116. For example, adigital numerical value representative of a setpoint temperature to bedisplayed may be determined based on a prior setpoint value and asaturating and continuous relationship between rotation input and thetemperature. The displayed value may be, e.g., numeric, textual orgraphical.

The processing system 3160 may further set a variable value inaccordance with a user selection. For example, a particular type of userinput (e.g., inwards pressure exertion) may be detected. A value of aselected variable may be determined based on, e.g., a prior ringrotation, displayed variable value, etc. The variable may then be set tothis value.

The processing system 3160, according to some embodiments, is capable ofcarrying out the governance of the operation of smart thermostat 102including the user interface features described herein. The processingsystem 3160 is further programmed and configured to carry out otheroperations as described further hereinbelow and/or in other ones of thecommonly assigned incorporated applications. For example, processingsystem 3160 is further programmed and configured to maintain and updatea thermodynamic model for the enclosure in which the HVAC system isinstalled, such as described in U.S. Ser. No. 12/881,463. According tosome embodiments, the wireless communications system 3166 is used tocommunicate with devices such as personal computers and/or otherthermostats or HVAC system components, which can be peer-to-peercommunications, communications through one or more servers located on aprivate network, and/or communications through a cloud-based service.

Hazard Detector Integration with Thermostat—Thermostat Displays HazardDetector—Detected Alerts

According to embodiments, the presentations on electronic display 3116may reflect information provided to smart thermostat 102 from othersmart devices (e.g., any of devices 104, 106, 108, 110, 112, 114, and/or116, and others) in the smart-home environment 100. For example, upondetecting notable events, conditions, etc. in the home, other smartdevices transmit information corresponding to the detected notableevents, conditions, etc. to smart thermostats 102, which displaycorresponding messages on electronic displays 3116.

As described with reference to FIG. 1, the smart devices in thesmart-home environment 100 are capable of data communications andinformation sharing with each other and with the central server orcloud-computing system 164. The data communications can be carried outusing any of a variety of custom or standard wireless protocols (Wi-Fi,ZigBee, 6LoWPAN, etc.) and/or any of a variety of custom or standardwired protocols (CAT6 Ethernet, HomePlug, etc.) As described, all orsome of the smart devices can serve as wireless or wired repeaters andcombine to create a mesh network in the smart-home environment 100. Inthe event one of the smart devices detects a notable condition or event,it can send a corresponding message over the mesh network, and the othersmart devices repeat the message, thereby causing the message to travelfrom smart device to smart device throughout the smart-home environment100 as well as over the Internet 162 to the central server orcloud-computing system 164.

As illustrated in FIGS. 32A-C, upon detecting an alarm condition, hazarddetector 104 sends a corresponding message that gets repeated throughthe mesh network to the one or more smart thermostats 102 located in thesmart-home environment 100. Hazard detector 104 may detect apre-hazardous or serious hazard condition that involves smoke, CO,and/or heat in a location of the home. In the event hazard detector 104detects a pre-hazardous condition for smoke in the bedroom, it sends acorresponding message through the mesh network to one or more smartthermostats 102, which display a corresponding message. As illustratedin FIG. 32A, the electronic display 3116 of smart thermostat 102displays a message 3205 saying, “There's smoke in the bedroom.” In theevent the smoke condition worsens and hazard detector 104 detects aserious hazard condition involving smoke in the bedroom, hazard detectorsends a corresponding message through the mesh network to one or moresmart thermostats 102, which display a corresponding message. Asillustrated in FIG. 32B, the electronic display 3116 of smart thermostat102 displays a message 3210 alerting users of the serious hazardcondition by saying, “SMOKE in the bedroom GET OUT NOW”.

Further, in the event hazard detector 104 determines that a previouslydetected alarm condition has cleared from a location, it sends acorresponding message through the mesh network to one or more smartthermostats 102, which display a corresponding message. For example, ifafter detecting a pre-hazardous or serious hazard condition involvingsmoke in the bedroom, hazard detector 104 later determines that thesmoke has cleared from the bedroom, it sends a corresponding message. Asillustrated in FIG. 32C, the electronic display 3116 of smart thermostat102 displays a message 3215 saying, “Smoke in the bedroom has cleared.”

As mentioned above, it should be appreciated that any of the smartdevices in the smart-home environment 100 can send messages to smartthermostats 102 for display. In one example, upon a motion detectordetermining that a window in home has been breached, it or other smartdevices in the home can send a corresponding message through the meshnetwork to smart thermostats 102, which, as illustrated in FIG. 32D, candisplay a message 3220 that says, “The window in the kids' bedroom hasbeen jimmied”.

In another example, smart doorbell 106 sends a message regarding aperson at the door through the mesh network to smart thermostats 102.According to embodiments, technologies and sensors at the smart doorbell106 may identify the person based on facial recognition or based onother characteristics such as “a signature” unique to the manner inwhich a particular person walks or otherwise moves when approaching thedoor. For example over time, based on input received from the smartdoorbell 106, a central server or the smart doorbell 106 itself canbuild up an address book of profile data about people who approach thedoor. The address book may comprise some identifying biometric data foreach person. For example, the address book can be built over time usinglow-resolution data such as ultrasonic, passive IR, etc. to create aunique signature for individuals. This becomes almost like a fingerprintregarding how that person approaches the house. In some instances, whena “familiar” person approaches the door, the smart doorbell 116 “asks”the person if he is “John Doe”, to which the person can verbally orphysically respond. Further, in addition to or instead of identificationbased on these unique “signatures”, individuals may enable their mobiledevices to communicate with the smart doorbell 116, such as viaBluetooth, NFC, or other wireless protocols. Also, for example,individual may “swipe” their smart phones in front of the smartdoorbell's RFID scanner.

Upon identifying the individual standing near or approach a door, smartdoorbell 106 may send a corresponding message through the mesh networkto one or more smart thermostats 102 in the smart-home environment 100.For example, the message may indicate that a person is at or approachingthe front door and the message may optionally include the person's nameand/or an image of the person. Responsive to receiving such a message,smart thermostats 102 display corresponding information on electronicdisplays 3116. As illustrated in FIG. 32E, electronic display 3116 ofsmart thermostat 102 displays a message 3205 that says, “John Doe is atthe door”.

Determining User Location and Displaying Corresponding Messages

According to embodiments, user location(s) can be determined,corresponding messages can be displayed on smart devices associated withthe smart-home environment 100, and inferences about CO sources andactions to be taken based on elevated CO levels can be adjustedaccording to the user location(s). For example, smart devices within thehome and/or the central server or cloud-computing system 164 obtainlocation data, such as GPS data, from computers 166 of users, some ofwhom may have registered their computers 166 with the smart home, smartdevices therein, and/or central server or cloud-computing system 164 asbeing associated with the smart-home environment 100. In some instancesthe central server or cloud-computing system 164 receivesoccupant-location data directly from the mobile devices, whereas inothers the data is received or inferred from an intermediary, such asone of the smart devices in the home.

In instances where occupant-location data is received directly from themobile device, the central server or cloud-computing system 164 candetermine if the occupant is “at home” or “away”, as explained below.When an occupant is at home, the central server or cloud-computingsystem 164 may be able to determine the occupant's actual room-location(e.g., bedroom, kitchen, garage, etc.). To do so, for example, thecentral server or cloud-computing system 164 cross-references theoccupant-location (e.g., GPS coordinates) with a map of the home.

In instances where occupant-location data is received from a smartdevice located within the home, the central server or cloud-computingsystem 164 can infer that the occupant is inside the home. Further, theroom-location of the occupants can be determined. For example, the smartwall switches 108, the smart wall plugs 110, the smart doorbells 106,and other smart devices in the smart-home environment 100 detect thepresence of the computer 166 of the user and transmit corresponding datato the central server or cloud-computing system 164. Such detection ofmobile devices can be accomplished using WiFi, Bluetooth, NFC, etc. Itshould also be appreciated that passive RFID tags can be used todetermine the room-location of occupants (and pets). For example, anRFID may be associated with one or more of the occupants (and pets) ofthe house, such as by including the tags in wallets, bracelets,wristbands, mobile devices, collars, etc. The smart devices in thevarious rooms detect the RFID tags, and send that information to thecentral server or cloud-computing system 164. It should be appreciatedthat, because they are typically mounted in unobstructed locations, highon walls of often-occupied rooms, smart hazard detectors 104 areparticularly well suited for RFID sensors.

In the example illustrated with reference to FIG. 26, the users includeWife 3314, Husband 3318 and Child 3322, all of whom have registeredtheir computers 166 with the central server or cloud-computing system164 (FIG. 1) as being associated with the smart-home environment 100.Further, two geo-location boundaries or “geo-fences” 3330, 3334 areregistered as being associated with the smart-home environment 100. Insome embodiments, the users, who are occupants of the home, define andregister the geo-fences, while in other embodiments the central serveror cloud-computing system 164 auto-generates the geo-fences for thehome.

Inner geo-fence 3330 defines the perimeter of living area of the home.The area within the inner-geo fence includes not only the home but alsothe land immediately surrounding the house, including any closelyassociated structures, such as garages or sheds (“the curtilage”). Outergeo-fence 3334 defines an outer perimeter, which is sometimes miles fromthe home. The outer geo-fence 3334 is adjustable and extends well beyondthe curtilage. For example, the perimeter defined by the outer geo-fence3334 may have a radius of two to three miles in some embodiments, whilein other embodiments the radius is larger or smaller.

According to embodiments, the central server or cloud-computing system164 infers that an occupant is “at home” when inside the inner geo-fence3330 and that the occupant is “away” when outside of the inner geo-fence3330. Further, the central server or cloud-computing system 164 infersan occupant is going home when the occupant moves (e.g., travels by car)from outside to inside the outer geo-fence 3334. As such, the centralserver or cloud-computing system 164 uses the inner geo-fence 3330 todetermine when occupants leave the home, and it uses the outer geo-fence1334 to determine when occupants are heading home.

Several exemplary smart-home objectives will now be described. In oneexample, when an inference is made that a user is heading home, acorresponding message may be displayed on smart thermostats 102. Forexample, upon inferring that Wife 3314 is heading home, a correspondingmessage can be send to smart thermostat 102 causing smart thermostat todisplay on electronic display 3116 a message that says, “Wife is headinghome”. Likewise, when an inference is made that Wife 3314 is leavinghome, a corresponding message can be displayed. When Wife 3314 arriveshome an moves to a position near a door of the home, a correspondingmessage can be sent to smart thermostat 102 causing smart thermostat todisplay a message that says, “Wife is at the door”. This inference canbe made when Wife 3314 moves to a position close to or within innergeo-fence 3330 or to a position close enough that a computer 166 of Wife3314 communicates with smart doorbell 106. Also for example, upondetecting that Child 3322 has moved into a different room of the home, acorresponding message can be sent to smart thermostat 102 causing smartthermostat to display a message that says, “Child is now in the kidsbedroom”. Room transitions, as discussed above, can be detected by smartdevices in the home according to a number of techniques, including thesmart devices communicating with the mobile device of the person makingthe transitions though the home. Further, as discussed above, GPS datacan be used to detected occupant movement within the home.

When locations of occupants (including guests) within smart-homeenvironment 100 can be determined with high confidence, significantenhancements to inferring causes and/or mitigating high CO levels may bepossible. For example, presence of one or more occupants in certainrooms may make causes of high CO levels more plausible, due for exampleto cooking activity, smoking, or use of a legacy (e.g., not “smart”)device such as a wood stove for heating. Such a scenario, if recurring,would most likely be recognizable within existing CO and homecharacteristic data as a likely cause for a high CO level. Also, knownpresence of one or more occupants may be used to elevate the importanceof clearing a room of CO when dangerously high levels are detected,especially when the occupant appears unresponsive. For example, when aspecific occupant's location is verifiable with high accuracy because ofa mobile device or RFID tag that the person is known to always have withhim/her, and that location has a high CO level, and there is no sign ofactivity from the occupant, very high priority can be placed on eithertrying to eliminate the source of the CO or to do everything possible toventilate the location.

Smart Keypad

In some embodiments a network-connected smart keypad is provided in thesmart-home environment 100. According to embodiments, an importantunderlying functionality of the smart keypad is to control thefunctionality of security features of the smart-home environment 100. Itshould be appreciated that the smart keypad is enhanced with a varietyof multi-sensing capabilities that, while indeed enhancing home safetyand security in many ways, can provide additional functionalitiesrelating to controlling the other smart devices in the home, HVACcontrol, home energy conservation, intra-home communications,entertainment, etc.

According to embodiments, smart keypad includes powering circuitry,including a rechargeable battery, for extracting power as needed fromthe 120V “hot” line voltage wire. The rechargeable battery can either beused as a conventional back-up source or as a reservoir to supply excessDC power if needed for short periods.

According to some embodiments, like other smart-home devices describedherein, the smart keypad is split into two parts: a head unit and abackplate. This bifurcation can increase the success and commerciallongevity of the smart keypads by making them a modular platformconsisting of two basic components. According to some embodiments, thebackplate is a permanent interface box (sometimes referred to herein as“docking station”) that serves as a physical connection into the walland to the 120V line voltage wires or other wiring of the smart-homeenvironment 100, and that contains AC-to-DC powering circuitry. Wheninstalled, the docking station may resemble a conventional one-gang ortwo-gang wall box, except no dangerous high-voltage wires are exposed tothe user. According to some embodiments, docking station also includes acellular wireless interface.

According to some embodiments, the head unit (sometimes referred toherein as “replacement module”) actually contains all of the sensors,processors, user interfaces, the rechargeable battery, and so forth.Users can plug and unplug the unit in and out of the docking station.Many different commercial and functional possibilities for provisioning,maintenance, and upgrade are possible. For example, after years of usingany particular head unit, a user will be able to buy a new version ofthe head unit and simply plug it into the docking station. There arealso many different versions for the head unit, such as an extremelylow-cost version that is nothing but a user interface, and then aprogression of increasingly-capable version, up to and includingextremely fancy head unit with small OLED televisions and high-fidelitymini-speakers. Thus, it should be appreciated that the various versionsof the head units of the smart keypads and other smart devices can allbe interchangeable, with any of them working when placed into anydocking station. This can advantageously encourage sharing andre-deployment of old head units—for example, when an importanthigh-capability head unit (for the kitchen or living room, for example)can replaced by a great new version of the head unit, then the old headunit can be re-deployed in a bedroom or a basement, etc. When firstplugged into a docking station, the head unit can ask the user (by 2DLCD display, 2D/3D holographic projection, voice interaction, etc.) afew simple questions such as, “Where am I” and the user can select“bedroom” or “living room” and so forth. In other examples, the headunit can provide instructions, such as “Press button once if I am in thekitchen, press twice if I am in the den, etc.”

According to some embodiments, the smart keypad contains a mainprocessor, storage, display and user interface, audio speaker,microphone, power converter, GPS receiver, RFID locater, and generalphysical module receiver. The smart keypad further contains wireless andwired networking. In view of the ample power availability, a variety ofcommunications capabilities can be provided, including Wi-Fi, ZigBee,3G/4G wireless, CAT6 wired Ethernet, and even optical fiber from thecurb. Furthermore, because the smart keypad can be connected to the home120V system, a HomePlug or other powerline-communications capability canbe provided. Accordingly, the smart keypad can be connected to andcommunicate with the other smart-home devices of the smart-homeenvironment 100 and to the central server or cloud-computing system 164.

The smart keypad can include any of the components (e.g., temperaturesensor, humidity sensor, occupancy sensor, ambient light sensor,communication equipment, processors, memory, etc.) that are included inany of the other smart-home devices (e.g., smart doorbells 106, smartthermostats 102, smart wall switches 108, smart wall plugs 110, etc.)described herein. In some embodiments, the smart keypad is hardwiredwith a battery backup. In some embodiments, the smart keypad isincorporated into the wall switch 108, whereas in other embodiments thesmart keypad can be its own device.

The smart keypad also includes sensors such as temperature, humidity,occupancy, ambient light, fire, smoke, carbon monoxide, activeproximity, passive infrared motion, ultrasound, CCD/video camera, etc.As mentioned above, a rechargeable battery is also included (orequivalently capable onboard power storage medium). For example, thebattery can be a rechargeable Lithium-Ion battery. In operation, thesmart keypad charges the battery during time intervals in which thehardware power usage is less than what power stealing can optimallyprovide, and that will discharge to provide the needed extra electricalpower during time intervals in which the hardware power usage is greaterthan what power stealing can optimally provide.

The user interface of the smart keypad can include one or more visualdisplays (LCD, TFT, OLED, etc.), touchscreen and/or button inputcapabilities, the audio speaker, and so forth. According to embodiments,an optional 2D image and/or 3D holographic image projector, can also beprovided so that the effective dimension of the display is not justlimited to the physical size of the smart keypad. The user interface canbe user customized by the home occupants.

The smart keypad can be secured by a user-determined passcode. In someembodiments, the passcode can be a PIN comprising any number andcombination of letters and/or numbers. In other embodiments, thepasscode can be a phrase. In yet other embodiments, the passcode can bea gesture, which the smart keypad senses using ultrasonic sensors, PIRsensors, etc. In still other embodiments, the passcode is in the form ofa unique connect-the-dot pattern, where the user interface displays aplurality of dots (e.g., a grid of dots) and the user moves his or herfinger from dot to dot in a unique pattern. Any one of these forms ofthe passcode, including the gesture and the connect-the-dots pattern,can provide users with a quick and easy way to arm and disarm the alarmsystem of the home. For example when leaving the home, the user can walkup to the smart keypad and make the unique gesture or input theconnect-the-dots pattern to arm the alarm. According to someembodiments, the smart keypad manages a user list, which includes a listof users and corresponding times they can control the keypad toarm/disarm the security system and to control other functions of thesmart home. In some cases, the various users may identify themselves tothe smart keypad using unique identification numbers and access codes,including the passcodes described above. Further, in some cases, thesmart keypad may be capable of recognizing a user based on the user's“digital fingerprint”, such as by wirelessly identifying the user'scomputer 166.

According to embodiments, the smart keypad includes a “light your path”feature, whereby the smart keypad activates a light when it senses thata user is approaching in darkness or near darkness. For example, in theevent the user approaches the smart keypad in the middle of the night,the smart keypad may activate nearby lights in the home or a lightincorporated in the smart keypad itself (e.g., LED) to provide a lightedpathway for the user. In one example, the smart keypad is incorporatedin a wall light switch, and the smart keypad activates the lightassociated with the wall switch when a user is approaching the smartkeypad. In some examples, upon detecting an approaching user when thesecurity system is armed, the smart keypad or other devices of the homeor the server 164 can send notification to the occupants' mobile devicesor other electronic devices. Also, for example, the smart keypad cansend a notification message to the occupants' mobile devices any timethe alarm system is armed or disarmed by a user.

According to embodiments, the smart keypad is “smash and bash”resistant. For example, in the event the home's alarm system is armedand the smart keypad is smash (e.g., by an intruder attempting to disarmthe alarm by bashing the keypad), the alarm remains armed. In somecases, upon being smashed, the smart keypad triggers the alarm andexecutes pre-configured actions, such as notifying police and/or otheremergency personnel.

According to embodiments, the smart keypad or other devices in the homeare capable of assigning user-defined gestures to actions or sets ofactions. For example, the user may program the smart keypad with a“panic gesture” that causes the smart keypad, other devices in the smarthome, or the server 164 to notify authorities, such as by calling orotherwise notifying medical, police, etc. Such a panic gesture may be,for example, the user quickly waving his or her hands in the air. Theuser may also program the smart keypad or other devices in the home withan audible panic command. For example, when the user yells “help”, thenmedical, police, etc. may be called or otherwise notified. In otherexamples, the smart keypad can include a panic button that the user canpress to call the police, medical, etc.

Displaying Messages on the Smart Keypad and Other Smart Devices

According to embodiments, the smart keypad or any of the othersmart-home devices have the ability to display or project messages, suchas via a display on the device itself or by projection. Messages may bedisplayable by the smart keypad, smart thermostat 102, or any of theother smart devices of the smart-home environment 100, according toembodiments. For example, when a person is at the front door, the smartkeypads, smart thermostats and other smart devices may display orproject a corresponding message, such as “Someone's at the door”. Thiswould be good for situations where the users have deactivated, or thesmart home has automatically deactivated, the doorbell and/or otheraudible notifications because some or all of the occupants are sleeping.These messages would also be useful for hearing impaired occupants. Alsofor example, the smart keypads, smart thermostats and other smartdevices may be configured to display or project safety and securitywarning messages, such as “Evacuate” due to possible intruder, fire, CO,etc. The message could be projected in large font on walls, floors,ceilings, etc. And the message could provide additional information. Forexample, the message could be “Intruder detected in den”, “Fire detectedin kitchen”, etc.

According to embodiments, the smart keypad and the other smart devicesare used as platforms for running home applications. For example, thesmart keypad has the capability of downloading and/or executingapplications that enable users to use the smart keypad to control theirsmart homes. For example, a user could install a “thermostat” app thatcan be accessed and controlled from any of the smart devices in thehome, including the smart keypads, to control the home's HVAC. Thus, forexample, a user interface could be provided on the smart keypad. Theuser could also install “security” and “safety” apps that communicatewith hazard detector and security device of the home, and displaymessages. It should be appreciated that the number and type of apps thatcould be download and installed are endless.

Various modifications may be made without departing from the spirit andscope of the invention. Indeed, various user interfaces for operatinghazard detectors, HVACs and other devices have been provided, yet theseare meant to be illustrative and not limiting as to the scope of theoverall invention. While methods and systems have been described forreceiving hazard detection and hazard detector status information, it iscontemplated that these methods may be applied to receive and/orcommunicate other information. It is to be further appreciated that theterm hazard detector, as used hereinabove and hereinbelow, can includehazard detectors having direct wired connection with hazard responsesystems, and can further include hazard detectors that do not connectdirectly with the hazard response systems, but that provide alertsconcerning detected potential hazard conditions.

Accordingly, the invention is not limited to the above-describedembodiments, but instead is defined by the appended claims in light oftheir full scope of equivalents.

What is claimed is:
 1. A method for determining one or more sources of carbon monoxide (CO) in a smart-home environment, the smart-home environment including a plurality of smart-home devices that have at least measurement and communication capabilities, the method comprising: linking each smart-home device of the plurality of smart-home devices with an online management account maintained by a cloud-computing system, wherein the cloud-computing system communicates with the plurality of smart-home devices via the Internet; registering a mobile device with the online management account maintained by the cloud-computing system, wherein the mobile device communicates with the cloud-computing system via the Internet; measuring a level of CO in the smart-home environment, by each smart-home device of the plurality of smart-home devices, to generate a plurality of CO measurements, wherein each smart-home device of the plurality of smart-home devices are located at different locations; providing the plurality of CO measurements and one or more current characteristics of the smart-home environment from one or more of the smart-home devices to an analyzing device; evaluating, by the analyzing device, based on the plurality of CO measurements and the one or more current characteristics of the smart-home environment, a set of CO correlation scenarios, wherein: each CO correlation scenario of the set of CO correlation scenarios indicates a corresponding specific CO source based on: smart device location, CO change trend, and the one or more current characteristics of the smart-home environment; selecting a specific CO source as the most likely source of the CO based on the evaluated set of CO correlation scenarios; and outputting a notification via the Internet to the mobile device that has been registered with the online management account with which the plurality of smart-home devices are linked, wherein the notification is indicative of the specific CO source as the most likely source of the CO.
 2. The method of claim 1, wherein a result of evaluating each CO correlation scenario of the set of CO correlation scenarios is generation of a confidence metric that the plurality of CO measurements are due to a corresponding specific CO source, the method further comprises: generating a sum of confidence metrics that correspond to a same specific CO source.
 3. The method of claim 2, wherein evaluating one or more of the CO correlation scenarios of the set of CO correlation scenarios comprises: generating a positive or negative result state for each of the one or more of the CO correlation scenarios of the set of CO correlation scenarios, and assigning a fixed value as the confidence metric responsive to generating the positive result state.
 4. The method of claim 2, wherein evaluating one or more of the CO correlation scenarios of the set of CO correlation scenarios comprises generating a variable result for each of the one or more of the CO correlation scenarios, and assigning a variable value that is responsive to a degree of fit between the plurality of CO measurements and the one or more current characteristics, as the confidence metric.
 5. The method of claim 2, wherein selecting one or more of the specific CO sources as the most likely source of the CO comprises comparing the sums of the confidence metrics for the corresponding CO sources and determining that one of the corresponding CO sources is more likely than all of the other sources.
 6. The method of claim 2, wherein selecting one or more of the CO specific sources as the most likely source of the CO comprises determining that two or more of the corresponding sources are possible CO sources, responsive to the sums of the confidence metrics for each of the two or more corresponding CO sources being within a confidence window of one another.
 7. The method of claim 1, wherein the analyzing device is a smart-home device of the plurality of smart-home devices that measures the CO, and others of the smart-home devices provide at least some of the current characteristics to the smart-home device that measures the CO.
 8. The method of claim 1, wherein the analyzing device is a computer that receives the plurality of CO measurements and the current characteristics.
 9. The method of claim 1, wherein: one of the CO correlation scenarios of the set of CO correlation scenarios includes CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a garage; the one or more current characteristics include a time of day; and the specific CO source is automobile exhaust in the garage.
 10. The method of claim 9, wherein the one or more current characteristics further include a day of the week.
 11. The method of claim 9, wherein the one or more current characteristics further include an indication that a door associated with the garage has opened or closed.
 12. The method of claim 1, wherein: one of the CO correlation scenarios of the set of CO correlation scenarios includes CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a kitchen; the one or more current characteristics include detection of a temperature increase in the kitchen; and the specific CO source is operation of a gas stove in the kitchen.
 13. The method of claim 12, wherein the one or more current characteristics further include detection of smoke in the kitchen.
 14. The method of claim 12, wherein the CO measurements taken by one or more smart-home devices of the plurality of smart-home devices in or adjacent to a kitchen rise rapidly, while CO measurements taken by other smart-home devices of the plurality of smart-home devices do not change significantly.
 15. The method of claim 1, wherein: one of the CO correlation scenarios of the set of CO correlation scenarios include CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a location of a wood burning appliance; the one or more current characteristics include: detection of a temperature increase in the location of the one or more smart-home device of the plurality of smart-home devices, and information that an HVAC system is not operating as a heat source; and the specific CO source is wood burning in the wood burning appliance.
 16. The method of claim 1, wherein: one of the CO correlation scenarios of the set of CO correlation scenarios includes CO measurements taken by one or more smart-home device of the plurality of smart-home devices in or adjacent to a location of a water heater; the one or more characteristics include detection of a humidity increase in or adjacent to a bathroom; and the specific CO source is a CO leak from the water heater.
 17. The method of claim 1, further comprising generating one of the CO correlation scenarios of the set of CO correlation scenarios by: periodically generating CO measurements by a hazard detector of the smart-home devices; storing the CO measurements; periodically generating current characteristics of the smart-home environment that are not the CO measurements; storing the current characteristics; and generating the one of the CO correlation scenarios by evaluating a correlation possibility between the CO measurements and one or more of the current characteristics, by: determining correlation of the CO measurements with the one or more of the current characteristics; and discarding the correlation possibility responsive to no correlation being present between the CO measurements and the one or more of the current characteristics included in the correlation possibility; or retaining the correlation possibility as the CO correlation scenario responsive to a correlation being present between the CO measurements and the one or more of the current characteristics included in the correlation possibility.
 18. The method of claim 17, wherein storing the CO measurements comprises associating each of the CO measurements with a corresponding time identifier and location of the hazard detector, and storing the current characteristics comprises associating each of the current characteristics with a corresponding time identifier and a location of one of the smart-home devices that generated the current characteristic.
 19. The method of claim 17, wherein: one of the correlation possibilities is generated by randomly correlating the CO measurements with ones of the current characteristics.
 20. A system for determining a source of carbon monoxide (CO) in a smart-home environment, the system comprising: a plurality of smart-home devices located in different locations within the smart-home environment, wherein each smart-home device of the plurality of smart-home devices comprises: one or more sensors; a wireless communication interface; and one or more processors, each of the smart-home devices of the plurality of smart-home devices being configured to measure a level of CO; a cloud-based computing system that links each smart-home device of the plurality of smart-home devices with an online management account and registers a mobile device with the online management account maintained by the cloud-based computing system, wherein the cloud-based computing system communicates with the plurality of smart-home devices and the mobile device via the Internet; and a processing system, wherein the processing system is configured to: receive a plurality of CO measurements and one or more current characteristics of the smart-home environment from one or more of the smart-home devices of the plurality of smart-home devices; evaluate, based on the plurality of CO measurements and the one or more current characteristics of the smart-home environment, a set of CO correlation scenarios, wherein: each CO correlation scenario of the set of CO correlation scenarios identifies a corresponding specific CO source based on: smart device location, CO change trend, and at least one of the current characteristics of the smart-home environment; select a specific CO source as the most likely source of the CO, based on the evaluated set of CO correlation scenarios; and cause a notification to be output via the Internet to the mobile device that has been registered with the online management account with which the plurality of smart-home devices are linked, wherein the notification is indicative of the specific CO source as the most likely source of the CO.
 21. The system for determining the source of CO in the smart-home environment of claim 20, wherein the processing system being configured to evaluate each CO correlation scenario comprises the processing system being configured to: generate a plurality of confidence metrics, each confidence metric of the plurality of confidence metrics corresponding to a specific CO correlation scenario of the set of CO correlation scenarios; and aggregate confidence metrics of the plurality of confidence metrics that correspond to a same specific CO source.
 22. The system for determining the source of CO in the smart-home environment of claim 21, wherein the processing system being configured to select the specific CO source as the most likely source of the CO comprises the processing system being configured to: compare the aggregated confidence metrics; and determine that the specific CO source is the most likely source of the CO based on the aggregated confidence metrics.
 23. The system for determining the source of CO in the smart-home environment of claim 20, wherein the processing system is incorporated as part of a smart home device.
 24. The system for determining the source of CO in the smart-home environment of claim 23, wherein the smart home device in which the processing system is incorporated is a carbon monoxide detector.
 25. The system for determining the source of CO in the smart-home environment of claim 20, wherein the processing system is incorporated as part of the cloud-based computing system.
 26. The system for determining the source of CO in the smart-home environment of claim 20, wherein the processing system is part of a distinct computerized system from the cloud-based computing system and the plurality of smart-home devices.
 27. The system for determining the source of CO in the smart-home environment of claim 20, wherein a first CO correlation scenario of the set of CO correlation scenarios comprises: at least some CO measurements of the plurality of CO measurements are taken in or adjacent to a garage; the one or more current characteristics comprises a time of day; and the specific CO source is automobile exhaust in the garage.
 28. The system for determining the source of CO in the smart-home environment of claim 27, wherein the one or more current characteristics comprises an indication that a garage door of the garage has opened or closed.
 29. The system for determining the source of CO in the smart-home environment of claim 20, wherein a first CO correlation scenario of the set of CO correlation scenarios comprises: at least some CO measurements of the plurality of CO measurements are taken in or adjacent to a kitchen; the one or more current characteristics comprise detection of a temperature increase in the kitchen; and the specific CO source is operation of a gas stove in the kitchen.
 30. The system for determining the source of CO in the smart-home environment of claim 20, wherein a first CO correlation scenario of the set of CO correlation scenarios comprises: at least some CO measurements of the plurality of CO measurements being taken in or adjacent to a location of a water heater; the one or more current characteristics comprise detection of a humidity increase in or adjacent to a bathroom; and the specific CO source is the water heater. 